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Article

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

1
School of Information Science and Technology, Beijing Forestry University, Beijing 100083, China
2
Engineering Research Center for Forestry-Oriented Intelligent Information Processing, National Forestry and Grassland Administration, Beijing 100083, China
3
3D Geoinformation Research Group, Faculty of Architecture and the Built Environment, Delft University of Technology, 2628 BL Delft, The Netherlands
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(18), 3089; https://doi.org/10.3390/rs12183089
Received: 2 September 2020 / Revised: 18 September 2020 / Accepted: 19 September 2020 / Published: 21 September 2020
(This article belongs to the Special Issue 3D Point Clouds in Forest Remote Sensing)
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 (R2), 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 R2, 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 R2, 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 R2, rBias, and CV-RMSE of DBH are 0.94, −5.01%, and 9.06%, respectively. The R2, 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. View Full-Text
Keywords: terrestrial laser scanning; AdQSM; destructive sampling; tree volume; above-ground biomass terrestrial laser scanning; AdQSM; destructive sampling; tree volume; above-ground biomass
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MDPI and ACS Style

Fan, G.; Nan, L.; Dong, Y.; Su, X.; Chen, F. AdQSM: A New Method for Estimating Above-Ground Biomass from TLS Point Clouds. Remote Sens. 2020, 12, 3089. https://doi.org/10.3390/rs12183089

AMA Style

Fan G, Nan L, Dong Y, Su X, Chen F. AdQSM: A New Method for Estimating Above-Ground Biomass from TLS Point Clouds. Remote Sensing. 2020; 12(18):3089. https://doi.org/10.3390/rs12183089

Chicago/Turabian Style

Fan, Guangpeng, Liangliang Nan, Yanqi Dong, Xiaohui Su, and Feixiang Chen. 2020. "AdQSM: A New Method for Estimating Above-Ground Biomass from TLS Point Clouds" Remote Sensing 12, no. 18: 3089. https://doi.org/10.3390/rs12183089

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