Giant redwoods (Sequoiadendron giganteum) are some of the UK’s largest trees, despite only being introduced in the mid-19th century. Given recent interest in planting redwoods in the UK, partly due to their carbon sequestration potential and also their undoubted public appeal, an understanding of their viability is important. However, little or no research has been conducted to quantitatively estimate their carbon uptake in UK conditions. We used 3D terrestrial laser scanning (TLS) to make detailed structure measurements of individual S. giganteum  trees at three sites, to estimate aboveground biomass (AGB) and annual biomass accumulation rates. We show that UK-grown S. giganteum can sequester carbon at a rate of 80 - 100 kg C year^-1, varying with climate, management and age. This accumulation rate is 2.5 and 20 times faster than commonly-grown UK plantation tree species. We develop new UK-specific allometric models for S. giganteumwhich fit observed AGB with r² > 0.93 and bias < 2% and can be used to estimate S. giganteum AGB more generally. S. giganteum appears to represent a small but potentially important addition to the UK’s carbon sequestration efforts and this work provides a baseline for estimating their longer term AGB and carbon sequestration capacity.

TLS data were collected at 3 different UK sites in April 2022 and April 2023. TLS data were collected with a RIEGL VZ-400i V-Line 3D TLS (RIEGL Laser Measurement Systems GmbH, 2017). The scanner has a range of ~700 m, beam divergence 0.35 milliradians and emits light at 1550 nm. At each location an upright scan and a scan at 90° tilt were taken. The angular resolution of each scan was 0.04°. The scanner was mounted on a tripod at 1.5 m above the ground. At Havering and Benmore, due to the avenue layout, scans were conducted ~10 m apart (Wilkes et al. 2017) down the centre of the avenue, and then at either side of each line of trees, to try to ensure full coverage around all trees. At Havering this was difficult due to the proximity of fences at some points. At Wakehurst trees were sampled in a radial pattern, again at ~10 m apart, with locations being chosen to try to ensure full coverage around all trees.

TLS scans from all positions were co-registered into point clouds for each plot using the Riegl RiSCAN PRO software (v 2.7.1). Individual tree point clouds were extracted manually from plot level point clouds using the segmentation tool in CloudCompare (v 2.12.0). Segmented point clouds of individual trees were extracted using the TLSeparation (Vicari et al., 2019) and TLS2trees (Wilkes et al. 2022) Python tools. The resulting point clouds are stored as basic ascii txt files, with columns comprising x, y, z in each case.

Point clouds are all ascii txt files, with columns comprising x, y, z in each case and can be opened using CloudCompare (v 2.12.0).