为提取人工林单木参数，SFM算法用来重新恢复原始倾斜像片点云。对DOM

To extract individual tree parameters, SFM algorithm is used to restore the original photograph inclined point cloud. And separately to the DOM by lidar DEM normalized data of a single timber divided, high single wood tree crown area. Individual tree height point cloud extracting variables and the crown area Found multiple stepwise linear regression, the model generating unit wood biomass and accuracy assessment.

In order to extract the artificial forest monowood parameter, the SFM algorithm is used to restore the original tilt edgy point cloud. The data of DOM and the deization of lidar DEM were divided into one wood respectively, and the height and crown area of the single wood tree were obtained. The height variable and crown area extracted by the single wood dot cloud are multi-step linear regression with the measured value, and the single-wood biomass model is generated and the accuracy is evaluated.

In order to extract the single tree parameters of plantation, SFM algorithm is used to restore the original slanted image point cloud. The height and crown area of the single tree are obtained by segmenting the DOM and the data normalized by lidar DEM. The height variable and crown area extracted from the single tree point cloud were regressed with the measured value in multiple stepwise linear regression, and the single tree biomass model was generated and the accuracy was evaluated.<br>