Advancing Stem Volume Estimation Using Multi-Platform LiDAR and Taper Model Integration for Precision Forestry

초록

Stem volume is a critical factor in managing and evaluating forest resources. At present, stem volume is commonly estimated indirectly by constructing a taper model that utilizes sampling, diameter at breast height (DBH), and tree height. However, these estimates are constrained by errors arising from spatial and stand environment variations as well as uncertainties in height measurements. To address these issues, this study aimed to accurately estimate stem volume using light detection and ranging (LiDAR) technology, a key tool in modern precision forestry. LiDAR data were used to build comprehensive three-dimensional models of forests with multi-platform LiDAR systems. This approach allowed for precise measurements of tree heights and stem diameters at various heights, effectively mitigating the limitations of earlier measurement methods. Based on these data, a Kozak taper curve was developed at the individual tree level using LiDAR-derived tree height and diameter estimates. Integrating this curve with LiDAR data enabled a hybrid approach to estimating stem volume, facilitating the calculation of diameters at points not directly identifiable from LiDAR data alone. The proposed method was implemented and evaluated for two economically significant tree species in Korea: Pinus koraiensis and Larix kaempferi. The RMSE comparison between the taper curve-based approach and the hybrid volume estimation method showed that, for Pinus koraiensis, the RMSE was 0.11 m3 using the taper curve-based approach and 0.07 m3 for the hybrid method, while for Larix kaempferi, the RMSE was 0.13 m3 and 0.05 m3, respectively. The estimation error of the hybrid method was approximately half that of the taper curve-based approach. Consequently, the hybrid volume estimation method, which integrates LiDAR and the taper model, overcomes the limitations of conventional taper curve-based approaches and contributes to improving the accuracy of forest resource monitoring.

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