DERIVATION OF FOREST INVENTORY PARAMETERS FOR CARBON ESTIMATION USING TERRESTRIAL LIDAR

Abstract. This research was conducted to derive forest sample plot inventory parameters from terrestrial LiDAR (T-LiDAR) for estimating above ground biomass (AGB)/carbon stocks in primary tropical rain forest. Inventory parameters of all sampled trees within circular plots of 500 m² were collected from field observations while T-LiDAR data were acquired through multiple scanning using Reigl VZ-400 scanner. Pre-processing and registration of multiple scans were done in RSCAN PRO software. Point cloud constructing individual sampled tree was extracted and tree inventory parameters (diameter at breast height-DBH and tree height) were measured manually. AGB/carbon stocks were estimated using Chave et al., (2005) allometric equation. An average 80 % of sampled trees were detected from point cloud of the plots. The average of plots values of R² and RMSE for manually measured DBHs were 0.95, 2.7 cm respectively. Similarly, the average of plots values of R² and RMSE for manually measured trees heights were 0.77, 2.96 m respectively. The average value of AGB/carbon stocks estimated from field measurements and T-LiDAR manually derived DBHs and trees heights were 286 Mg ha-1 and 134 Mg ha⁻¹; and 278 M ha-1 and 130 Mg ha⁻¹ respectively. The R² values for the estimated AGB and AGC were both 0.93 and corresponding RMSE values were 42.4 Mg ha⁻¹ and 19.9 Mg  ha⁻¹ respectively. AGB and AGC were estimated with 14.8 % accuracy.