机载LIDAR点云数据估测单株木生物量

Estimating biomass of individual trees using point cloud data of airborne LIDAR

使用黑河流域遥感-地面观测同步试验获取的机载激光雷达(LIDAR)点云数据估测了典型树种的单株木生物量。首先由点云数据生成冠层高度模型(CHM),然后采用优化的单株木树冠特征识别算法估测相关的结构参数,最后通过回归分析建立估测参数(树高、冠幅)与实测参数(树高、冠幅、胸径)之间的最优回归方程,并与现有的单株木生物量实测相关生长方程联立,得到单株木生物量估测相关生长方程。结果表明,由LIDAR点云数据得到的单株木估测参数与实测参数显著相关,可以估测单株木生物量(R^2为0.729)。

The representative species＇ biomass of individual trees was estimated using the point cloud data from airborne light detection and ranging （LIDAR） obtained by the simultaneous remote sensing and ground-based experiment in the Heihe River Basin. Firstly, the canopy height model （CHM） was created from the point cloud data. Then, the relatively structural parameters were extracted using the optimized algorithm of crown feature recognition of individual trees. Finally, the optimal regression equations between the estimated parameters （such as tree heights, crown diameters） and the field-measured parameters （such as tree heights, crown diameters, diameters at breast height （DBHs）） were obtained by the linear regression analysis, and they were combined with the allometric growth equations of the field-measured biomass of individual trees to get the allometric growth equations of estimated biomass of individual trees. In conclusion, the correlation is obvious between the field-measured parameters and the estimated parameters of individual trees from point cloud data, which can be used to estimate biomass of individual trees （R2 is 0.729）.