Sample Plots Forestry Parameters Verification and Updating Using Airborne LiDAR Data

The rapid development of LiDAR technology has promoted great changes in forest resource surveys. airborne point cloud can provide the precise height and detailed structure trees, estimate key indicators such as stock volume, diameter at breast height, biomass a large scale. By establishing relationship models between parameters sample plots calculated LiDAR, these developments may eventually expand to large-scale surveys entire areas. In this study, eight northeast China are used verify update information using obtained by scanner riegl-vq-1560i. First, tree crowns segmented profile-rotating algorithm, positions registered based on dominant heights. Second, considering correlation crown shape species, we use DBN classifier identify species features crowns, which extracted 1D array. Third, when is known, width, biomass, volume be from enabling accurate data. Finally, experiment results demonstrate that F-score segmentation exceed 0.95, accuracy correction exceeds 90%, R2 east–west north–south aboveground 0.893, 0.757, 0.694, 0.840, 0.896 0.891, respectively. above indicate LiDAR-based survey practical widely applied monitoring.