AdQSM: A New Method for Estimating Above-Ground Biomass from TLS Point Clouds

被引:77
作者
Fan, Guangpeng [1 ,2 ]
Nan, Liangliang [3 ]
Dong, Yanqi [1 ]
Su, Xiaohui [1 ,2 ]
Chen, Feixiang [1 ,2 ]
机构
[1] Beijing Forestry Univ, Sch Informat Sci & Technol, Beijing 100083, Peoples R China
[2] Natl Forestry & Grassland Adm, Engn Res Ctr Forestry Oriented Intelligent Inform, Beijing 100083, Peoples R China
[3] Delft Univ Technol, Fac Architecture & Built Environm, 3D Geoinformat Res Grp, NL-2628 BL Delft, Netherlands
关键词
terrestrial laser scanning; AdQSM; destructive sampling; tree volume; above-ground biomass; FOREST BIOMASS; ALLOMETRIC MODELS; STEM VOLUME; ERROR PROPAGATION; INDIVIDUAL TREES; TERRESTRIAL; LIDAR; TOOL;
D O I
10.3390/rs12183089
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Forest above-ground biomass (AGB) can be estimated based on light detection and ranging (LiDAR) point clouds. This paper introduces an accurate and detailed quantitative structure model (AdQSM), which can estimate the AGB of large tropical trees. AdQSM is based on the reconstruction of 3D tree models from terrestrial laser scanning (TLS) point clouds. It represents a tree as a set of closed and complete convex polyhedra. We use AdQSM to model 29 trees of various species (total 18 species) scanned by TLS from three study sites (the dense tropical forests of Peru, Indonesia, and Guyana). The destructively sampled tree geometry measurement data is used as reference values to evaluate the accuracy of diameter at breast height (DBH), tree height, tree volume, branch volume, and AGB estimated from AdQSM. After AdQSM reconstructs the structure and volume of each tree, AGB is derived by combining the wood density of the specific tree species from destructive sampling. The AGB estimation from AdQSM and the post-harvest reference measurement data show a satisfying agreement. The coefficient of variation of root mean square error (CV-RMSE) and the concordance correlation coefficient (CCC) are 20.37% and 0.97, respectively. AdQSM provides accurate tree volume estimation, regardless of the characteristics of the tree structure, without major systematic deviations. We compared the accuracy of AdQSM and TreeQSM in modeling the volume of 29 trees. The tree volume from AdQSM is compared with the reference value, and the determination coefficient (R-2), relative bias (rBias), and CV-RMSE of tree volume are 0.96, 6.98%, and 22.62%, respectively. The tree volume from TreeQSM is compared with the reference value, and the R-2, relative Bias (rBias), and CV-RMSE of tree volume are 0.94, -9.69%, and 23.20%, respectively. The CCCs between the volume estimates based on AdQSM, TreeQSM, and the reference values are 0.97 and 0.96. AdQSM also models the branches in detail. The volume of branches from AdQSM is compared with the destructive measurement reference data. The R-2, rBias, and CV-RMSE of the branches volume are 0.97, 12.38%, and 36.86%, respectively. The DBH and height of the harvested trees were used as reference values to test the accuracy of AdQSM's estimation of DBH and tree height. The R-2, rBias, and CV-RMSE of DBH are 0.94, -5.01%, and 9.06%, respectively. The R-2, rBias, and CV-RMSE of the tree height were 0.95, 1.88%, and 5.79%, respectively. This paper provides not only a new QSM method for estimating AGB based on TLS point clouds but also the potential for further development and testing of allometric equations.
引用
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页数:22
相关论文
共 57 条
[1]   Developing Allometric Equations for Teak Plantations Located in the Coastal Region of Ecuador from Terrestrial Laser Scanning Data [J].
Aguilar, Fernando J. ;
Nemmaoui, Abderrahim ;
Penalver, Alberto ;
Rivas, Jose R. ;
Aguilar, Manuel A. .
FORESTS, 2019, 10 (12)
[2]   Automatic tree species recognition with quantitative structure models [J].
Akerblom, Markku ;
Raumonen, Pasi ;
Makipaa, Raisa ;
Kaasalainen, Mikko .
REMOTE SENSING OF ENVIRONMENT, 2017, 191 :1-12
[3]   Analysis of Geometric Primitives in Quantitative Structure Models of Tree Stems [J].
Akerblom, Markku ;
Raumonen, Pasi ;
Kaasalainen, Mikko ;
Casella, Eric .
REMOTE SENSING, 2015, 7 (04) :4581-4603
[4]  
ATTIWILL PM, 1968, FOREST SCI, V14, P13
[5]   Effects of Measurement Errors on Individual Tree Stem Volume Estimates for the Austrian National Forest Inventory [J].
Berger, Ambros ;
Gschwantner, Thomas ;
McRoberts, Ronald E. ;
Schadauer, Klemens .
FOREST SCIENCE, 2014, 60 (01) :14-24
[6]   Non-destructive tree volume estimation through quantitative structure modelling: Comparing UAV laser scanning with terrestrial LIDAR [J].
Brede, Benjamin ;
Calders, Kim ;
Lau, Alvaro ;
Raumonen, Pasi ;
Bartholomeus, Harm M. ;
Herold, Martin ;
Kooistra, Lammert .
REMOTE SENSING OF ENVIRONMENT, 2019, 233
[7]  
Calders K., 2015, P SILV 2015
[8]   Realistic Forest Stand Reconstruction from Terrestrial LiDAR for Radiative Transfer Modelling [J].
Calders, Kim ;
Origo, Niall ;
Burt, Andrew ;
Disney, Mathias ;
Nightingale, Joanne ;
Raumonen, Pasi ;
Akerblom, Markku ;
Malhi, Yadvinder ;
Lewis, Philip .
REMOTE SENSING, 2018, 10 (06)
[9]   Nondestructive estimates of above-ground biomass using terrestrial laser scanning [J].
Calders, Kim ;
Newnham, Glenn ;
Burt, Andrew ;
Murphy, Simon ;
Raumonen, Pasi ;
Herold, Martin ;
Culvenor, Darius ;
Avitabile, Valerio ;
Disney, Mathias ;
Armston, John ;
Kaasalainen, Mikko .
METHODS IN ECOLOGY AND EVOLUTION, 2015, 6 (02) :198-208
[10]   Estimating canopy structure and biomass in bamboo forests using airborne LiDAR data [J].
Cao, Lin ;
Coops, Nicholas C. ;
Sun, Yuan ;
Ruan, Honghua ;
Wang, Guibin ;
Dai, Jinsong ;
She, Guanghui .
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2019, 148 :114-129