Individual tree segmentation and biomass estimation based on UAV Digital aerial photograph

Digital aerial photograph (DAP) data is processed based on Structure from Motion (SfM) algorithm and regional net adjustment method to generate digital surface discrete point clouds similar to Light Detection and Ranging (LiDAR) and digital orthophoto mosaic (DOM) similar to optical remote sensing image. In this study, we obtained high-resolution images of mature forests of Chinese fir by unmanned aerial vehicle (UAV) flying through cross-route flight, and then reconstructed the three-dimensional point clouds in the UAV aerial area by SfM technique. The point cloud segmentation (PCS) algorithm was used for the individual tree segmentation, and the F-score of the three sample plots were 0.91, 0.94, and 0.94, respectively. Individual tree biomass modeling was conducted using 155 mature Chinese fir forests which were correctly segmented. The relative root mean squared error (rRMSE) values of random forest (RF), bagged tree (BT) and support vector regression (SVR) were 34.48%, 35.74% and 40.93 %, respectively. Our study demonstrated that DAP point clouds had great potential to extract forest vertical parameters and could be applied successfully in individual tree segmentation and individual tree biomass modeling.