面向农业地面车辆的基于相机的植被指数测绘系统用于植物生长估计
Plant Growth Estimation with a Camera-Based Vegetation Index Mapping System for Agricultural Ground Vehicles
- Technical University of Munich（慕尼黑工业大学）
- Munich Institute of Robotics and Machine Intelligence (MIRMI)（慕尼黑机器人与机器智能研究所）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
本研究开发了一种可搭载于农业地面车辆的基于相机的植被指数测绘系统，采用RTK-GNSS与透视投影实现实时植物生长估计，经与商用传感器对比验证，趋势一致且可过滤地面非地面区域以降低作物密度影响。
AI中文摘要：
本研究提出一种基于相机的传感器，用于测绘农田内的植物生长情况，该传感器可搭载于拖拉机等地面车辆，依靠RTK-GNSS将多张多光谱图像准确合并为一张地图。采用NDVI作为估计植物生长的指数，根据相机类型也可使用其他指数。相机拍摄的图像通过透视投影映射到估计的地面平面，这种计算简单的方法即使在低端硬件上也能对农田中的所有图像进行实时处理。将该结果与商用成熟的车载传感器进行对比，绝对值难以直接比较，但两种传感器显示出相似的趋势。该基于相机的方法还可对地面与非地面区域进行过滤，有望降低作物密度对平均测量NDVI的影响。
英文摘要：
This work presents a camera-based sensor for mapping plant growth over an agricultural field. The sensor can be used on ground-based vehicles like a tractor and relies on RTK-GNSS to correctly merge many multispectral images onto one map. NDVI is used as an index to estimate plant growth, but the approach can be used with other indices as well depending on the camera. The images from the camera are projected onto the estimated ground plane using perspective projection. This computationally simple approach allows for real-time processing of all images on the field even with low-end hardware. The results are compared to a commercially established vehicle-mounted sensor. Absolute values are hard to compare, but both sensors show similar trends. The camera-based approach also allows for filtering of ground and non-ground areas, potentially reducing the impact of crop density on the average measured NDVI.
