A new method to estimate branch biomass from terrestrial laser scanning data by bridging tree structure models

Background and AimsBranch biomass and other attributes are important for estimating the carbon budget of forest stands and characterizing crown structure. As destructive measuring is time-consuming and labour-intensive, terrestrial laser scanning (TLS) as a solution has been used to estimate branch biomass quickly and non-destructively. However, branch information extraction from TLS data alone is challenging due to occlusion and other defects, especially for estimating individual branch attributes in coniferous trees.MethodsThis study presents a method, entitled TSM_tls, to estimate individual branch biomass non-destructively and accurately by combining tree structure models and TLS data. The TSM_tls method constructs the stem-taper curve from TLS data, then uses tree structure models to determine the number, basal area and biomass of individual branches at whorl level. We estimated the tree structural model parameters from 122 destructively measured Scots pine (Pinus sylvestris) trees and tested the method on six Scots pine trees that were first TLS-scanned and later destructively measured. Additionally, we estimated the branch biomass using other TLS-based approaches for comparison.Key ResultsTree-level branch biomass estimates derived from TSM_tls showed the best agreement with the destructive measurements coefficient of variation of root mean square error (CV-RMSE) = 9.66 % and concordance correlation coefficient (CCC) = 0.99], outperforming the other TLS-based approaches (CV-RMSE 12.97–57.45 % and CCC 0.43–0.98 ). Whorl-level individual branch attributes estimates produced from TSM_tls showed more accurate results than those produced from TLS data directly.ConclusionsThe results showed that the TSM_tls method proposed in this study holds promise for extension to more species and larger areas.