Calibration of local, regional or global allometric equations to estimate biomass at the tree level constitutes a significant burden on projects aiming at reducing Carbon emissions from forest degradation and deforestation. The objective of this contribution is to assess the precision and accuracy of Terrestrial Laser Scanning (TLS) for estimating volumes and above‐ground biomass (AGB) of the woody parts of tropical trees, and for the calibration of allometric models. We used a destructive dataset of 61 trees, with diameters and AGB of up to 186.6 cm and 60 Mg respectively, which were scanned, felled and weighed in the semi‐deciduous forests of eastern Cameroon. We present an operational approach based on available software allowing the retrieving of TLS volume with low bias and high accuracy for large tropical trees. Edition of the obtained models proved necessary, mainly to account for the complexity of buttressed parts of tree trunks, which were separately modelled through a meshing approach, and to bring a few corrections in the topology and geometry of branches, thanks to the amapstudio‐scan software. Over the entire dataset, TLS‐derived volumes proved highly reliable for branches larger than 5 cm in diameter. The volumes of the remaining woody parts estimated for stumps, stems and crowns as well as for the whole tree proved very accurate (RMSE below 2.81% and R² above of .98) and unbiased. Once converted into AGB using mean local‐specific wood density values, TLS estimates allowed calibrating a biomass allometric model with coefficients statistically undistinguishable from those of a model based on destructive data. The Unedited Quantitative Structure Model (QSM) however leads to systematic overestimations of woody volumes and subsequently to significantly different allometric parameters. We can therefore conclude that a non‐destructive TLS approach can now be used as an operational alternative to traditional destructive sampling to build the allometric equations, although attention must be paid to the quality of QSM model adjustments to avoid systematic bias.

(1) Terrestrial laser scanning (TLS) technology is a powerful tool for assessing tree growth based on time series analysis, as it allows a level of scrutiny not achievable using established destructive techniques. We applied TLS technology to 21 wild cherry trees grown in a research plot near Breisach (southern Germany) in order to build quantitative structure models (QSMs) for each tree. Scans were carried out over three subsequent years (2012-2014), so that three QSMs per each tree were constructed. Using the above approach, we were able to assess the annual growth of the individual wild cherry trees in terms of diameter and height, stem and branch volume, and the merchantable timber fraction. In addition, the growth of single branches of sample trees was detected and quantified. The availability of QSMs based on TLS-derived data allowed the accurate determination of crown length and width, as well as the volume reduction as the result of the tree pruning applied after the first scan (2012). The aboveground biomass (AGB) was assessed for each tree based on the QSM-derived volume and published wood density values for wild cherry, and then compared with AGB values estimated with standard allometric methods, obtaining a very high correlation (r 2 adj = 0.941). We concluded that the proposed approach is an effective non-destructive technique to accurately assess the increase of tree biomass, and discuss its future application in the forestry sector.

Many analyses in ecology and forestry require wood volume estimates of trees. However, non-destructive measurements are not straightforward because trees are differing in their three-dimensional structures and shapes. In this paper we compared three methods (one voxel-based and two cylinder-based methods) for wood volume calculation of trees from point clouds obtained by terrestrial laser scanning. We analysed a total of 24 young trees, composed of four different species ranging between 1.79 m to 7.96 m in height, comparing the derived volume estimates from the point clouds with xylometric reference volumes for each tree. We found that both voxel-and cylinder-based approaches are able to compute wood volumes with an average accuracy above 90% when compared to reference volumes. The best results were achieved with the voxel-based method (r 2 = 0.98). Cylinder-model based methods (r 2 = 0.90 and 0.92 respectively) did perform slightly less well but offer valuable additional opportunities to analyse structural parameters for each tree. We found that the error of volume estimates from point clouds are strongly species-specific. Therefore, species-specific parameter sets for point-cloud based wood volume estimation methods are required for more robust estimates across a number of tree species.

Aim of study: To assess terrestrial laser scanning (TLS) accuracy in estimating biometrical forest parameters at plot-based level in order to replace manual survey for forest inventory purposes.Area of study: Monte Morello, Tuscany region, ItalyMaterial and methods: In 14 plots (10 m radius) in dense Mediterranean mixed conifer forests, diameter at breast height (DBH) and height were measured in Summer 2016. Tree volume was computed using the second Italian National Forest Inventory (INFC II) equations. TLS data were acquired in the same plots and quantitative structure models (QSMs) were applied to TLS data to compute dendrometric parameters. Tree parameters measured in field survey, i.e. DBH, height, and computed volume, were compared to those resulting from TLS data processing. The effect of distance from the plot boundary in the accuracy of DBH, height and volume estimation from TLS data was tested.Main results: TLS-derived DBH showed a good correlation with the traditional forest inventory data (R2=0.98, RRMSE=7.81%), while tree height was less correlated with the traditional forest inventory data (R2=0.60, RRMSE=16.99%). Poor agreement was observed when comparing the volume from TLS data with volume estimated from the INFC II prediction equations.Research highlights: The study demonstrated that the application of QSM to plot-based terrestrial laser data generates errors in plots with high density of coniferous trees. A buffer zone of 5 m would help reduce the error of 35% and 42% respectively in height estimation for all trees and in volume estimation for broadleaved trees.