Modeling Biometric Attributes from Tree Height Using Unmanned Aerial Vehicles (UAV) in Natural Forest Stands

Abstract

This study estimated biometric attributes of individual trees from the automated measurement of tree height (THUV) by using images from unmanned aerial vehicles (UAVs). An experiment was carried out in a natural forest stand in the north of Mexico by using a DJI P4 multispectral equipment and regression analysis. The results show that total tree height (TH) is successfully estimated from UAV images, as the automated estimation of total height (THUV) reaches a R2 = 0,95 and a RMSE = 0,36 m. Consequently, THUV was statistically reliable to generate allometric equations (R2 > 0,57) regarding the canopy height model (CH), diameter at breast height (DBH), basal diameter (BD), above-ground biomass (AGB), volume (V), and carbon contents (C). It is concluded that the estimation of total height with UAVs is a viable option to improve efficiency in forest inventories. However, increased efforts towards the configuration of modern technologies and statistical algorithms are needed; future research challenges remain, particularly in the densest forests areas.