Rapid Estimation of Forest Aboveground Biomass by Integrating Drone and Backpack LiDAR Data
CUI Qinghua
LIANG Zhaodong
ZHANG Xingan
HU Tianyu
LI Zhuoqing
Abstract：Accurately,efficiently,and rapidly obtaining information on the aboveground biomass and related resources of artificial forests,as well as monitoring structural changes,is crucial for the effective management and utilization of forest resources.This study focused on the Forest Farm in Wudi County,Binzhou City,Shandong Province,where we combined drone and backpack LiDAR technologies to develop a fast method for estimating aboveground biomass of forests.By integrating data from both drone and backpack LiDAR,we achieved precise estimates of aboveground biomass at the individual tree scale across the entire forest area.The backpack LiDAR data revealed that the diameter at breast height(DBH)ranged from 2.10 cm to 33.50 cm,with an average of 11.40 cm.Tree height ranged from 2.00 m to 10.20 m,with an average of 6.46 m.Using this data,we constructed a localized allometric equation for tree height and DBH,achieving a fitting accuracy of 0.81.The canopy height model generated by the drone LiDAR successfully segmented 55,060 trees,and by combining this with the localized allometric equation,we estimated the DBH of the trees.Finally,using allometric equations from the literature that relate biomass to tree height and DBH,we calculated the biomass of individual trees.The results indicated that the average aboveground biomass per tree in this area was 36.42 kg,with a maximum of 334.84 kg,and the total biomass amounts to 1,717,034.17 kg.The integration of backpack and drone LiDAR technologies not only enhances the efficiency and accuracy of forest surveys but also paves the way for sustainable forest resource management.
Keywords：BiomassLiDARAllometric EquationDroneBackpack
Publication Date：2025-04-28
Online Publishing Date：2026-05-22(First online date of this platform, not the publication date of the document)
Pages：9( 9-17 )