Estimating the Leaf Area of Urban Individual Trees From Single-Scan Terrestrial Laser Scanner Based on Slant Leaf Area Index

Individual trees are fundamental to urban ecosystems as they play an important role in energy transfer, pollutant removal, and habitat formation. Leaf area (LA) is an important factor to quantify the effect of individual trees on urban ecosystems. Terrestrial laser scanners (TLSs) are widely recognized as the most accurate devices for tree structural measurements. However, they face challenges in estimating LA from LA index (LAI) for individual trees primarily due to arbitrary and confusing horizontal projection areas. Occlusion and clumping effects further hinder the objective and accurate LA measurements of individual trees. Therefore, we developed the slant leaf area index-based method (SLAIM) to estimate the LA of individual trees from single-scan TLS data by introducing the concept of slant leaf area index (SLAI). SLAI quantifies the amount of leaves along the view direction, and it can be retrieved at given view zeniths using gap probability. Subsequently, LA can be accumulated by SLAI across the whole crown. Tests with simulated and field-measured TLS point clouds demonstrate SLAIM's accuracy, with the relative errors (REs) in LA below 10% in most cases. Stratified LA validation reveals an R^{2} exceeding 0.77 across all realistic crowns, along with a root-mean-square error (RMSE) under 2 m2. SLAIM's advantages include compatibility with single-scan point clouds, effective correction of clumping effects, and consideration of variations in leaf projection coefficients at different zeniths. SLAIM proves more efficient and practical for actual LA measurements, showcasing its potential for advanced urban ecosystem research.