Speaker
Description
Accurate single-tree volume estimation is fundamental to forest inventory and operational planning in timber harvesting. Conventional volume estimation relies on field-measured tree dimensions such as diameter at breast height (DBH), tree height, and occasionally upper-stem diameters, which are labour-intensive and costly to acquire at scale. Mobile laser scanning (MLS) offers an efficient means of capturing below-crown stem geometry in boreal forests, yet its potential for supporting volume prediction through integration with biometric models has received limited attention. This study evaluates the feasibility of single-tree volume estimation by combining MLS-derived stem diameter profiles with a semi-parametric taper model. Three MLS measurement configurations of increasing stem coverage were compared on 50 Scots pine (Pinus sylvestris) trees in a managed stand in Eastern Finland: (1) MLS-derived DBH only, (2) MLS stem profile from 0 to 2 m, and (3) MLS stem profile from 0 to 5 m. Stem volume was computed by numerical integration of the reconstructed taper curve. Reference volumes were obtained from a taper model calibrated with field-measured DBH, tree height, and upper-stem diameter (d6). As a cross-check, Laasasenaho’s three-variable volume equation using the same field inputs was also evaluated.
Volume prediction improved systematically with increasing MLS stem coverage. The DBH-only configuration produced a relative RMSE of 26.1% with a negative bias, indicating that DBH alone provides insufficient geometric information for reliable volume estimation. Extending the MLS profile to 0–2 m reduced relative RMSE to 13.4%, and further extension to 0–5 m achieved a relative RMSE of 10.2%, with 74% of trees predicted within 10% of the reference volume. Laasasenaho’s equation showed close agreement with the taper-integrated reference (relative RMSE 5.1%), supporting internal consistency of the field-based benchmark under standard Finnish volume modelling practice. These results demonstrate that MLS-based below-crown stem profiles, when integrated with appropriate biometric models, can yield operationally useful single-tree volume estimates. The approach offers a practical basis for developing efficient ground-LiDAR inventory workflows, with potential applications in pre-harvest assessment and stand-level growing stock estimation.
| Keywords | operations; taper; pine; inventory |
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