Assessment of understory vegetation in a plantation forest of the southeastern United States using terrestrial laser scanning

• DOI: 10.1016/j.ecoinf.2023.102254
• Publication Date: 2023-08-07T16:00:27Z
• Authors: Angel Adhikari; Alicia Peduzzi; Cristian R. Montes; Nathaniel Osborne; Deepak R. Mishra
• Keywords: Understory; Forest Inventory; Laser Scanning

Forests of the southeastern United States are home to large timber industries with substantial contributions global round wood production and paper products. Despite success plantations in this area, pine growth remains constrained due competition between planted species understory. Moreover, effective control interspecies had shown a significant two- four-times increase stand productivity. Thus, study aims evaluate use laser scanning derived data from Terrestrial Laser Scanner (TLS) assess understory vegetation biomass, as conventional methods utilizing optical imagery have yet be quantifying mapping evergreen coastal forests States. For study, we utilized TLS scan entire forest profile within 60 sample plots an operational loblolly plantation Nassau County, Florida, collected biomass through destructive sampling. We compared three TLS-based volume estimation for predicting applied Adaptive Least Absolute Shrinkage Selection Operator (ALASSO) regression method derive optimal model by integrating most efficient other TLS-derived standard metrics. Our identifies 20th percentile echo height 3D metric based on mean cover explanatory variables model. The exhibits high accuracy, Adjusted R-squared (Adj. R2) 0.80 Root Mean Square Error (RMSE) 234.8 g per square meter (g/m2). Additionally, understory-based outperformed methods, such voxel count dimensional (3D) alpha hall-based method, Adj. R2 0.79, 0.47, 0.57, RMSE values 288, 448.6, 413 g/m2, respectively, when used single variable resulting successfully predicted quantified vegetation, showcasing TLS's potential accurately capture variation, particularly evergreen-dominated regions. As tool monitoring understory, can aid managers identifying areas that require measures enhanced management practices.