A hybrid method for forest aboveground biomass estimation: Fusion of individual tree- and area-based approaches over northeast China

Currently, the large-scale above-ground biomass (AGB) estimation primarily relies on area-based approach (ABA). With advancements in individual tree detection technology and multi-platform remote sensing data availability, individual tree-based approach (ITA) offer new potential for accurate and non-destructive AGB estimation. However, research on integrating ITA with ABA for scaling AGB estimates from individual trees to the regional level remains limited. This study introduced an innovative hybrid framework incorporating ITA and ABA for regional scale estimation of forest AGB through the combination of handheld, unmanned, and satellite LiDAR and Landsat 8 imagery. We provide the handheld and unmanned LiDAR data collected in northeast China.