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.