Estimation of Single Tree Factor of Eucalyptus by Merging Airborne and Backpack LiDAR

doi:10.13466/j.cnki.lyzygl.2022.06.020

Abstract

Abstract:

We investigated the applicability of fused data in forest resource surveys by fusing backpack LiDAR and airborne LiDAR point cloud data to estimate the single wood factor of eucalyptus trees in four eucalyptus plantations in Wuzhishan City,Hainan Province,with a total of 157 eucalyptus trees. A comparison of the results with the actual sample plots showed that the fused point cloud data had an R²=0.982 and RMSE=0.868cm for the estimation of diameter at breast height,and R²=0.895 and RMSE=2.005m for the estimation of tree height,which was better than that of the high accuracy of the tree obtained using only backpack LiDAR data (R²=0.835 and RMSE=2.458m).This study demonstrated that backpack LiDAR-based point cloud data was more accurate in obtaining single wood diameter at breast height,and that fused point cloud data could improve the estimation of tree height from single backpack point cloud data.

Key words: backpack LiDAR, airborne LiDAR, single wood parameters, diameter at breast height, tree height

CLC Number:

S758

ZHANG Xinjie, ZHENG Yanfeng, WEN Kunjian, WANG Pengjie, WU Fayun. Estimation of Single Tree Factor of Eucalyptus by Merging Airborne and Backpack LiDAR[J]. FOREST RESOURCES WANAGEMENT, 2022, (6): 131-137.

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References 21

[1]	庞勇, 李增元, 陈尔学, 等. 激光雷达技术及其在林业上的应用[J]. 林业科学, 2005, 41(3):129-136.
[2]	郭庆华, 刘瑾, 李玉美, 等. 生物多样性近地面遥感监测:应用现状与前景展望[J]. 生物多样性, 2016, 24(11):1249-1266. doi: 10.17520/biods.2016059
[3]	Zhao K, Suarez J C, Garcia M, et al. Utility of multitemporal lidar for forest and carbon monitoring:Tree growth,biomass dynamics,and carbon flux[J]. Remote Sensing of Environment, 2018,204,883-897.
[4]	Matasci G, Hermosilla T, Wulder M A, et al. Large-area mapping of Canadian boreal forest cover,height,biomass and other structural attributes using Landsat composites and lidar plots[J]. Remote Sensing of Environment, 2018, 209:90-106. doi: 10.1016/j.rse.2017.12.020
[5]	曾伟生, 孙乡楠, 王六如, 等. 基于激光雷达数据的东北林区航空林分材积表编制[J]. 林业资源管理, 2021(1):147-155.
[6]	孙忠秋, 高金萍, 吴发云, 等. 基于机载激光雷达点云和随机森林算法的森林蓄积量估测[J]. 林业科学, 2021, 57(8):68-81.
[7]	周蓉, 赵天忠, 吴发云. 依据BP神经网络的机载LiDAR数据估算林分平均高[J]. 东北林业大学学报, 2021, 49(9):60-66.
[8]	黄侃, 于强, 黄华国. 基于机载CCD和ALS伪波形数据的山区地表分类研究[J]. 农业机械学报, 2020, 51(3):201-208.
[9]	黄华国. 林业定量遥感研究进展和展望[J]. 北京林业大学学报, 2019, 41(12):1-14.
[10]	Su Y, Guo Q, Jin S, et al. The development and evaluation of a backpack LiDAR system for accurate and efficient forest inventory[J]. IEEE Geoscience and Remote Sensing Letters, 2021, 18(9):1660-1664. doi: 10.1109/LGRS.2020.3005166
[11]	Xie Y, Zhang J, Chen X, et al. Accuracy assessment and error analysis for diameter at breast height measurement of trees obtained using a novel backpack LiDAR system[J]. Forest Ecosystems, 2020, 7(1):7-33. doi: 10.1186/s40663-020-0216-9
[12]	黄旭, 贾炜玮, 王强, 等. 背包式激光雷达的落叶松单木因子提取[J]. 森林工程, 2019, 35(4):14-21.
[13]	Xu D, Wang H, Xu W, et al. LiDAR applications to estimate forest biomass at individual tree scale:Opportunities,challenges and future perspectives[J]. Forests, 2021, 12(5):550. doi: 10.3390/f12050550
[14]	符国瑷, 冯绍信. 海南五指山森林的垂直分布及其特征[J]. 广西植物, 1995(1):57-69.
[15]	刘迎春, 吴发云, 孙忠秋, 等. 陆地生态系统碳监测卫星多载荷替代数据海南综合试验[J]. 林业资源管理. 2021(4):138-148.
[16]	Zhao X, Guo Q, Su Y, et al. Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2016, 117:79-91. doi: 10.1016/j.isprsjprs.2016.03.016
[17]	Tao S, Wu F, Guo Q, et al. Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2015, 110:66-76. doi: 10.1016/j.isprsjprs.2015.10.007
[18]	Hyyppä E, Yu X, Kaartinen H, et al. Comparison of backpack,handheld,under-canopy UAV,and above-canopy UAV laser scanning for field reference data collection in boreal forests[J]. Remote Sensing, 2020, 12(20):3327. doi: 10.3390/rs12203327
[19]	Hyyppä E, Kukko A, Kaijaluoto R, et al. Accurate derivation of stem curve and volume using backpack mobile laser scanning[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 2020, 161:246-262. doi: 10.1016/j.isprsjprs.2020.01.018
[20]	Ko C, Lee S, Yim J, et al. Comparison of forest inventory methods at plot-level between a backpack personal laser scanning(BPLS)and conventional equipment in jeju island,South Korea[J]. Forests, 2021, 12(3):308. doi: 10.3390/f12030308
[21]	Hartley R J L, Jayathunga S, Massam P D, et al. Assessing the potential of backpack-mounted mobile laser scanning systems for tree phenotyping[J]. Remote Sensing, 2022, 14(14):3344. doi: 10.3390/rs14143344

样地编号	单木株数/株	胸径范围/cm	树高范围/m	平均胸径/cm	平均树高/m	郁闭度
1	36	7.5~30.0	6.2~25.2	20.1	19.2	0.6
2	23	12.6~44.2	7.0~35.0	27.1	26.5	0.4
3	62	8.3~25.1	9.2~23.5	13.9	16.7	0.7
4	38	9.1~20.9	9.9~29.7	15.0	19.8	0.5

设备参数	数值
激光扫描器	Velodyne VLP-16 x 2
激光器扫描距离/m	100
激光波长/nm	903
扫描频率/(pts/s)	600000
水平视场角/(°)	0~360
垂直视场角/(°)	-90~90
LiDAR精度/cm	±3
相对精度/cm	3
绝对精度/cm	5

样地编号	单木株数/株	点云分割株数/株			召回率/%	精确率/%
样地编号	单木株数/株	正确分割(TP)	漏分割(FN)	错误分割(FP)	召回率/%	精确率/%
1	36	36	0	3	100.00	92.31
2	23	23	0	2	100.00	92.00
3	62	61	1	4	98.39	93.85
4	38	38	0	1	100.00	97.44