UWA School of Agriculture and Environment, The University of Western Australia, Crawley, Stirling Highway, WA 6009, Australia.
Australian Herbicide Resistance Initiative, The University of Western Australia, Crawley, Stirling Highway, WA 6009, Australia.
Sensors (Basel). 2021 Mar 26;21(7):2328. doi: 10.3390/s21072328.
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 plot where 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.
传统的大田均匀喷洒除草方法需要大量的除草剂投入，成本高昂，对环境也有影响。因此，一些更为集中的杂草控制方法，如精准杂草管理（SSWM），变得越来越受欢迎，但这些方法需要识别杂草位置的方法。技术的进步为自动化方法（如无人机）提供了可能性，但也需要地面传感器来检测和绘制杂草地图。在本研究中，评估了激光雷达（LiDAR）传感器检测和定位杂草的能力。为此，进行了两次试验，使用不同高度和直径的人工目标（代表杂草）来了解 LiDAR 的检测极限。结果表明，LiDAR 不同扫描距离处目标的可检测性直接受到目标大小及其相对于 LiDAR 的方向的影响。第三次试验是在麦田中进行的，LiDAR 用于扫描作物冠层上方不同高度的不同杂草物种，以验证固定 LiDAR 在田间情况下检测杂草的能力。结果表明，基于与作物冠层的高度差异，LiDAR 检测到麦田中 100%的杂草。
