A Density-Based Approach for Leaf Area Index Assessment in a Complex Forest Environment Using a Terrestrial Laser Scanner

A novel density-based approach using terrestrial laser scanning (TLS) demonstrates high accuracy and efficiency for estimating Leaf Area Index (LAI) in structurally complex forest environments. The method, tested in Hawaii Volcanoes National Park, achieved 90% accuracy with a low root mean square error (RMSE) of 0.31, outperforming traditional manual methods. By leveraging the Compact Biomass Lidar (CBL), the study differentiated foliar and woody materials through point density analysis and edge detection, revealing that woody materials exhibit higher reflectance at 905 nm compared to leaves. The approach, validated against field-measured LAI data, showed consistent performance across subsets of plots spaced 30 meters apart, with R² values ranging from 0.84 to 0.96. This method offers a rapid, cost-effective solution for precise forest structural assessment in diverse ecosystems.

Rouzbeh Kargar, A., MacKenzie, R., Asner, G. P., & van Aardt, J. (2019). A Density-Based Approach for Leaf Area Index Assessment in a Complex Forest Environment Using a Terrestrial Laser Scanner. Remote Sensing, 11(15), 1791. https://doi.org/10.3390/rs11151791