A brief overview and perspective of using airborne Lidar data for forest biomass estimation

Integration of Handheld and Airborne Lidar Data for Dicranopteris Dichotoma Biomass Estimation in a Subtropical Region of Fujian Province, China

“…The ALS data had point density of over 50 pt/m 2 . The preprocessing of ALS data was conducted using LiDAR360 software, including mosaicking of point clouds, denoising, filtering, and normalizing [17]. The point cloud filtering was used to classify the Lidar point clouds into ground and non-ground points, the denoising tool was used to remove low points, air noise, and isolated points, and others like power lines that were identified visually and then removed.…”

“…Use of sample plots for biomass estimation modeling often faces two challenges: the sufficient number of samples and spatially good representativeness, which is often difficult for collection of sample plots in field work. In general, sample plots from field measurements are directly used as modeling samples for developing biomass estimation models based on remote sensing data, even Lidar data [13,17]. However, the limited number of sample plots for modeling often results in relatively poor performance, especially when the model is used for prediction in the study area due to the fact that sample plots lack representation.…”

“…Because optical or SAR data mainly capture the canopy surface features, it is difficult to use them to estimate understory biomass. The Lidar technology, due to its ability in accurately capturing three-dimensional forest stand features, becomes an important data source for biomass estimation [17], especially for the understory vegetation.…”

“…Thus, they are often used to extract individual tree parameters such as diameter at breast height (DBH), tree height, and crown size. Other common Lidar data sources are airborne Lidar, especially the unmanned aerial vehicle (UAV), which obtain high density of point clouds valuable for extraction of tree or canopy height in a relatively large area [17]. To take advantages of terrestrial laser scanning (TLS) and UAV Lidar data, Panagiotidis et al [21] fused them together and improved extraction accuracies of tree metrics, such as DBH, tree height, crown projection area, crown width/length, 3D crown surface, and 3D crown volume.…”