共享多平台激光雷达点云数据对于开展森林生态以及激光雷达算法研究具有重要意义。为此，中国林业科学研究院资源信息研究所发布了亚热带林区的有人机、无人机和地基多平台激光雷达森林样地点云，以及地面调查基准数据集。数据集在中国广西国有高峰林场获取，包括桉树、杉木和马尾松3个树种，共25块样地。地面调查数据包括样地位置、树木位置、胸径、树高、枝下高和冠幅。该数据集可用于剖析不同平台激光雷达表征森林三维结构信息的特点，评估点云配准、单木分割等点云处理算法性能，分析森林结构参数提取的适用性，为区域、样地和单木尺度森林研究提供重要参考。此外，本研究发展了一种基于地基激光雷达点云的地面调查方法。该方法根据树干点云标记树木位置，并基于树木位置图进行每木检尺，记录树木参数，避免了实地单木定位和标记步骤，提高了作业效率，为林业地面调查提供一种新思路。

Sharing multi-platform light detection and ranging (LiDAR) point clouds of forests is of great significance for LiDAR remote sensing research and applications in forestry. To this end, the Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, has constructed a multi-platform LiDAR point cloud dataset for forest plots in subtropical regions, featuring airborne laser scanning, unmanned aerial vehicle laser scanning, and terrestrial laser scanning (TLS) point clouds, along with forest inventory data. The dataset was collected at Gaofeng Forest Farm in Guangxi, China, covering 25 plots with three tree species: Eucalyptus, Chinese fir, and Pinus massoniana. The field forest inventory data include plot locations, tree positions, diameter at breast height, tree height, height to the first live branch, and crown width. The dataset enables analysis of forest three-dimensional structural information captured by LiDAR from various platforms, evaluating automated processing algorithms like point cloud registration and tree segmentation. It provides important references for forest research at regional, plot, and tree levels. Additionally, this study developed a ground survey method guided by TLS data. This method utilizes tree stem point clouds to mark tree positions and measures individual trees according to tree maps, improving operational efficiency.