Using Mathematical Models Based On Unmanned Aerial Vehicle Optical Imagery to Estimate Tree and Stand Characteristics

Abstract

This study continues the research in a 100-year-old black pine forest, consisting of stands with different structures. A sample was selected, consisting of six sampling plots (30 subsampling plots) with 508 trees for which the diameter (d), the height (h), and the crown diameter (cw) were measured. Models were generated at sample level (general models), as well as at stand level, based on the cw measured in the field. The general models estimated the sample volume at a relative RMSE (RMSE %) of 20.1% and those adapted to the stand structure at an RMSE of 2.8%. At the level of the sampling plots, the general models underestimated the volume of the higher productivity stands by 24% and overestimated the volume of the lower productivity stands by 27%.

Estimating tree volume based on crown mapping by UAV pictures in the Amazon Forest

“…The fits were satisfactory according to the analyzed statistics when comparing the results obtained with other studies. Tudoran (2022) found an RMSE of 13.7%, which can be explained by the use of the cd variable only as a linear function in estimating the diameter, and the diameter classes in the model in this study were associated in addition to cd. When Tudoran et al (2021) used a third-degree polynomial function using cd as a variable, it resulted in RMSE values which varied between (0.32 -0.89).…”