Comprehensive Dataset of Multi-source Large-footprint LiDAR for Typical Temperate Forests Based on the L-IFS Framework

This dataset is designed to support the validation of the LBI-based individual tree to footprint scaling (L-IFS) framework. The dataset covers three typical temperate forest study sites, namely Saihanba in China, Harvard Forest in the United States, and Canton Aargau in Switzerland. It provides aboveground biomass (AGB) reference samples derived from airborne small-footprint LiDAR (ALS and ULS) point clouds to support large-footprint LiDAR AGB estimation.Specifically, the collection contains over 20,000 footprint-level records, offering matched AGB reference values for platforms including GEDI, TECIS, and LVIS. Additionally, it includes raw full-waveform signals from TECIS, along with derived waveform metrics for both TECIS and LVIS. All spatial coordinates have been geolocation-refined using elevation profile matching. By integrating multi-source point cloud data, this dataset serves as a robust foundation for large-scale forest biomass estimation, full-waveform parameter analysis, and cross-platform LiDAR algorithm validation.本数据集旨在支撑基于LBI的单木-足迹尺度转换（L-IFS）框架的验证工作。数据集覆盖了三个典型温带森林研究站点，分别为中国塞罕坝、美国哈佛森林以及瑞士阿尔高州。数据集提供了源自机载小足迹激光雷达（ALS与ULS）点云的地上生物量（AGB）参考样本，用于支撑大足迹激光雷达的AGB估算任务。具体而言，该数据集包含超过20000条足迹级记录，可为GEDI、TECIS、LVIS等平台提供匹配的AGB参考值。此外，数据集还包含TECIS平台的原始全波形信号，以及TECIS与LVIS平台的衍生波形指标。所有空间坐标均通过高程剖面匹配完成了地理定位精校正。通过整合多源点云数据，本数据集可为大规模森林生物量估算、全波形参数分析以及跨平台激光雷达算法验证提供坚实的研究基础。