【摘要】 林冠结构与地形因子共同影响着森林重要物种资源及生境的时空变化,而针对我国地带性森林生态系统高精度林冠结构和地形数据集极为缺乏。基于近地面遥感平台获取的激光雷达数据,可以获取精确的林冠结构和地形数据。本研究以位于钱江源国家公园核心保护区的24公顷亚热带常绿阔叶林动态监测样地为研究对象,对该区域2018年基于近地面遥感技术获取的激光雷达点云数据进行计算分析及质量控制,获取该样地的林冠结构和地形数据。通过实时动态测量(RTK)的地面数据对数字高程模型(DEM)进行精度检验和验证,表明DEM的高程中误差为0.07米,数据具有较高精度。古田山24公顷亚热带常绿阔叶林动态监测样地为典型的中亚热带低海拔常绿阔叶林,本数据集可以为亚热带常绿阔叶林生物多样性监测和研究提供数据支撑。更多还原

【Abstract】 The canopy structure and topographic variables jointly influence the spatiotemporal variation of habitats for important species. However, there remains a considerable scarcity of precise forest canopy structure and topographic data obtained from large-scale forest dynamic plots. Li DAR data, acquired via near-surface remote sensing platforms, enables the precise calculation of canopy structure and topographic variables. This study selected the 24-hectare subtropical evergreen broad-leaved forest dynamic plot located in the core conservation area of Qianjiangyuan National Park as the research object. The point cloud data obtained in 2018 based on near-surface remote sensing platform for this area was analyzed and quality-controlled to acquire canopy structure and topography data. Ground data collected through Real-Time Kinematic(RTK) surveying were used to verify and validate the accuracy of the digital elevation model(DEM). The analysis revealed mean square error of elevation was 0.07 meters, suggesting a high level of accuracy of the dataset. The 24-hectare subtropical evergreen broad-leaved forest dynamic plot represents a typical low-altitude evergreen broad-leaved forest in the central subtropical region. This dataset can provide essential data support for the monitoring and research of biodiversity in subtropical broadleaved evergreen forests.更多还原