Above-ground biomass references for urban trees from terrestrial laser scanning data

Abstract

Background and Aims Within extending urban areas, trees serve a multitude of functions (e.g. carbon storage, suppression of air pollution, mitigation of the ‘heat island’ effect, oxygen, shade and recreation). Many of these services are positively correlated with tree size and structure. The quantification of above-ground biomass (AGB) is of especial importance to assess its carbon storage potential. However, quantification of AGB is difficult and the allometries applied are often based on forest trees, which are subject to very different growing conditions, competition and form. In this article we highlight the potential of terrestrial laser scanning (TLS) techniques to extract highly detailed information on urban tree structure and AGB. Methods Fifty-five urban trees distributed over seven cities in Switzerland were measured using TLS and traditional forest inventory techniques before they were felled and weighed. Tree structure, volume and AGB from the TLS point clouds were extracted using quantitative structure modelling. TLS-derived AGB estimates were compared with AGB estimates based on forest tree allometries dependent on diameter at breast height only. The correlations of various tree metrics as AGB predictors were assessed. Key Results Estimates of AGB derived by TLS showed good performance when compared with destructively harvested references, with an R2 of 0.954 (RMSE = 556 kg) compared with 0.837 (RMSE = 1159 kg) for allometrically derived AGB estimates. A correlation analysis showed that different TLS-derived wood volume estimates as well as trunk diameters and tree crown metrics show high correlation in describing total wood AGB, outperforming tree height. Conclusions Wood volume estimates based on TLS show high potential to estimate tree AGB independent of tree species, size and form. This allows us to retrieve highly accurate non-destructive AGB estimates that could be used to establish new allometric equations without the need for extensive destructive harvesting.

Tree Measurements in the Urban Environment: Insights from Traditional and Digital Field Instruments to Smartphone Applications

“…The potential of this methodology deserves thorough evaluation in future studies to extract highly detailed information about the structure of urban trees and a comparison with terrestrial laser scanner applications (Hu et al 2018;Kükenbrink et al 2021).…”

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

“…Two QSM methods (TreeQSM (Raumonen et al, 2013) and SimpleForest (Hackenberg et al, 2015)) and one hybrid voxelisation method (outer hull modelling, Stovall et al, 2017) were used to obtain volume estimates. All studies were conducted in forest environments, except Kükenbrink et al (2021) who sampled urban trees. All studies applied a tree‐centred scanning approach sensu Wilkes et al (2017), except for the data collected in Demol, Calders, Verbeeck, and Gielen (2021), who applied a grid‐wise procedure.…”

“…Site location of the destructive harvesting experiments included in the meta‐analysis. Data from Hackenberg et al (2015); Calders et al (2015); Stovall et al (2017); Lau et al (2019); Kükenbrink et al (2021); Demol, Calders, Verbeeck, and Gielen (2021); Momo Takoudjou et al (2018); Burt et al (2021). GDT = Gonzalez de Tanago et al (2018).…”

Terrestrial laser scanning: a new standard of forest measuring and modelling?

“…The use of UAV-LS provides an additional intermediate scale ( Brede et al , 2019 ). In cities and within urban forests, laser scanning provides a convenient tool for measuring tree attributes with less demand for destructive harvesting ( Kükenbrink et al , 2021 ).…”

“…Other articles in this issue elucidate multiple sides of current progress in the use and development of TLS and related methods for 3D forest dynamics. They cover TLS sampling strategies ( Boucher et al , 2021 ), automatic tree segmentation from MLS data ( Bienert et al , 2021 ), branch ( Hu et al , 2021 ) and above-ground ( Demol et al , 2021 ; Kükenbrink et al , 2021 ) biomass estimation, TLS data processing ( Martin-Ducup et al , 2021 ), effects of species mixing on stand productivity ( Pretzsch and Schütze, 2021 ), tree crown interactions ( van der Zee et al , 2021 ), and using TLS for developing models to investigate ecological and evolutionary processes ( O’Sullivan et al , 2021 ).…”