Plot-level wood-leaf separation for terrestrial laser scanning point clouds

With the increasing use of terrestrial laser scanning (TLS) technology in the field of forest ecology, wood-leaf separation for TLS point clouds of forest plots has attracted a large number of studies. This dataset was open to the public for the developing, testing and comparision of the wood-leaf separation methods for TLS data. The dataset was collected from three forest plots of different stem density, topography and tree species, i.e., a white birch (Betula papyrifera) plot, a Dahurian larch (Larix gmelinii) plot and a Chinese scholar tree (Styphnolobium japonicum) plot. The wood and leaf points were classified manually, which can be as the reference for method validation.随着地面激光扫描（Terrestrial Laser Scanning，TLS）技术在森林生态学领域的应用愈发广泛，森林样地地面激光扫描点云的木叶分离任务已吸引大量研究关注。本数据集面向公众开放，旨在支撑地面激光扫描数据木叶分离方法的开发、测试与对比验证工作。数据集采集自3个立木密度、地形特征与树种组成均存在差异的森林样地，分别为白桦（Betula papyrifera）样地、兴安落叶松（Larix gmelinii）样地和国槐（Styphnolobium japonicum）样地。所有木质点与叶片点均经人工标注分类，可作为木叶分离方法验证的参考基准。