Estimating forest above‐ground biomass with terrestrial laser scanning: Current status and future directions

Abstract

Improving the global monitoring of above‐ground biomass (AGB) is crucial for forest management to be effective in climate mitigation. In the last decade, methods have been developed for estimating AGB from terrestrial laser scanning (TLS) data. TLS‐derived AGB estimates can address current uncertainties in allometric and Earth observation (EO) methods that quantify AGB. We assembled a global dataset of TLS scanned and consecutively destructively measured trees from a variety of forest conditions and reconstruction pipelines. The dataset comprised 391 trees from 111 species with stem diameter ranging 8.5 to 180.3 cm and AGB ranging 13.5–43,950 kg. TLS‐derived AGB closely agreed with destructive values (bias <1%, concordance correlation coefficient of 98%). However, we identified below‐average performances for smaller trees (<1,000 kg) and conifers. In every individual study, TLS estimates of AGB were less biased and more accurate than those from allometric scaling models (ASMs), especially for larger trees (>1,000 kg). More effort should go to further understanding and constraining several TLS error sources. We currently lack an objective method of evaluating point cloud quality for tree volume reconstruction, hindering the development of reconstruction algorithms and presenting a bottleneck for tracking down the error sources identified in our synthesis. Since quantifying AGB with TLS requires only a fraction of the efforts as compared to destructive harvesting, TLS‐calibrated ASMs can become a powerful tool in AGB upscaling. TLS will be critical for calibrating/validating scheduled and launched remote sensing initiatives aiming at global AGB mapping.

Strong impacts of lianas on tree allometry lead to overestimation of tropical forest carbon stocks and sink

“…We conducted this study on the 50 ha forest dynamic plot on Barro Colorado Island (BCI), Panama (Supplementary section S1 for study site description). We quanti ed the impact of lianas on individual tree height, crown structure and biomass from the 3D TLS data [19]. We then scaled the individual tree-level observations to site-level to quantify the liana-induced carbon stock and accumulation reduction.…”

“…TLS-derived allometry reveals that the current levels of liana infestation reduces the stand-level carbon stocks on BCI by an average 5.3% (+/-3%). TLS-derived biomass estimates are unbiased and more accurate across a variety of forest ecosystems than allometry-derived estimates [19]. TLS data show that pantropical models including only DBH and wood density systematically overestimate tree biomass on BCI, even for liana-free trees, with more severe overestimation in liana-infested trees (Fig.…”

“…For buttressed trees, we estimated the volume of the trunk from the base up to the rst branching point using the triangulation function implemented in the TreeQSM algorithm [37]. Aboveground biomass estimated from this algorithm has been successfully validated against ground-truth biomass data derived from multiple destructive harvesting experiments across different tropical forest sites [19]. Figures of tree point clouds and QSMs can be found in the Supplementary section S4.…”

Improving quantitative structure models of trees inspired by pipe and metabolic scaling theory

“…Since around a decade various software tools to produce so called Quantitative Structure Models (QSMs) have been published (Demol et al, 2022a). QSMs consist of thousands and sometimes even ten or hundred thousands cylinders (Markku et al, 2015).…”

“…Also TreeQSM (Raumonen et al, 2013(Raumonen et al, , 2015 and 3dForest (Trochta et al, 2017) are QSM producing tools which can be downloaded with their source code being free. The free tools have been tested by comparing QSM estimated Volume derived from TLS data versus destructive collected Volume field measurements (Hackenberg et al, 2021;Demol et al, 2022a).…”