Integration of Aerial Mapping using UAV and Low-cost Backpack LiDAR for Biomass and Carbon Stock Estimation Calculation - Q. P. A. N. Ila; M. N. Cahyadi; H. H. Handayani; A. B. Raharjo; R. Mardiyanto; I. W. Farid; D. Saptarini; E. E. Saratoga (The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences)
The total forest area in Indonesia reaches 62.97% of Indonesia's land area or approximately 125.76 hectares, requiring effective and accurate inventory methods. Conventional methods have a high level of accuracy but require large costs and labor. The use of UAV (Unmanned Aerial Vehicles) and Backpack LiDAR technology has emerged as an efficient alternative solution for forest inventory. The UAV serves as an aerial image capture platform that generates orthomosaic and canopy height data through the Canopy Height Model (CHM). Meanwhile, Backpack LiDAR can generate detailed point cloud data that enables stem diameter (DBH) measurement and Above-Ground Biomass (AGB) estimation. The analysis showed that the backpack LiDAR had an RMSE error of 0.793 meters and a standard deviation of 0.30332 cm for DBH. Linear regression showed a relationship between DBH and AGB with an R2 of 0.5591, indicating DBH had a significant effect on AGB. These data were used to calculate carbon stocks, which had small differences between the manual and backpack LiDAR methods. The results show that this technology-based method can improve efficiency and accuracy in forest inventory and support climate change mitigation efforts.