Weeds and weed control are major production costs in global agriculture, with increasing challenges associated with herbicide‐based management because of concerns with chemical residue and herbicide resistance. Non‐chemical weed management may address these challenges but requires the ability to differentiate weeds from crops. Harvest is an ideal opportunity for the differentiation of weeds that grow taller than the crop, however, the ability to differentiate late‐season weeds from the crop is unknown. Weed mapping enables farmers to locate weed patches, evaluate the success of previous weed management strategies, and assist with planning for future herbicide applications. The aim of this study was to determine whether weed patches could be differentiated from the crop plants, based on height differences. Field surveys were carried out before crop harvest in 2018 and 2019, where a total of 86 and 105 weedy patches were manually assessed respectively. The results of this study demonstrated that across the 191 assessed weedy patches, in 97% of patches with Avena fatua (wild oat) plants, 86% with Raphanus raphanistrum (wild radish) plants and 92% with Sonchus oleraceus L. (sow thistles) plants it was possible to distinguish the weeds taller than the 95% of the crop plants. Future work should be dedicated to the assessment of the ability of remote sensing methods such as Light Detection and Ranging to detect and map late‐season weed species based on the results from this study on crop and weed height differences.

Conventional methods of uniformly spraying fields to combat weeds, requires large herbicide inputs at significant cost with impacts on the environment. More focused weed control methods such as site‐specific weed management (SSWM) have become popular but require methods to identify weed locations. Advances in technology allows the potential for automated methods such as drone, but also ground‐based sensors for detecting and mapping weeds. In this study, the capability of Light Detection and Ranging (LiDAR) sensors were assessed to detect and locate weeds. For this purpose, two trials were performed using artificial targets (representing weeds) at different heights and diameter to understand the detection limits of a LiDAR. The results showed the detectability of the target at different scanning distances from the LiDAR was directly influenced by the size of the target and its orientation toward the LiDAR. A third trial was performed in a wheat plotwhere the LiDAR was used to scan different weed species at various heights above the crop canopy, to verify the capacity of the stationary LiDAR to detect weeds in a field situation. The results showed that 100% of weeds in the wheat plot were detected by the LiDAR, based on their height differences with the crop canopy.

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