虽然Lidar点云数据已被广泛应用于获取森林各项结构参数,但这些方法并不适合于低矮的灌丛、林地和农作物。本文以玉米为研究对象,提出利用机载Lidar点云数据的强度信息和全波形数据中的距离与扫描天顶角信息,反演农作物覆盖度和LAI的方法。在黑河进行的飞行实验和地面验证表明,该方法具有较高精度,也表明Lidar在低矮自然植被监测和农业应用上有较大潜力。

Light detection and ranging (Lidar) point cloud data contains the information of the 3D coordinate and intensity, which can be applied to acquire the height of crown, fractional cover etc. in high-statue vegetation, such as the forest. Meanwhile, with the improvement of data storage capacity and processing speed, small footprint airborne Lidar is able to store the entire refl ected waveform through digitally sampling, which expands the application of Lidar. However, the methods used in forest are not suitable for shrubs, crops and other low canopies. In this paper, we choose the cron as the study object, and propose a crop fractional cover and leaf area index (LAI) retrieval method using airborne Lidar intensity of ground hits and the distance and zenith angle information contained in waveforms data. Relevant fi ght experiment and ground measurements in Heihe indicate that the method is reliable, and the experiment also validates the great potential for Lidar to be applied to monitor low natural vegetation in agriculture.