Real-time measurement of individual tree structure parameters based on augmented reality in an urban environment

Abstract

The rapid and accurate acquisition of tree structural parameters is a challenging task in urban tree inventories. Here, we developed a mobile application based on augmented reality (AR) called ARTreeWatch to measure individual tree height (TH) and diameter at breast height (DBH) using an Android smartphone. For the experiments, we installed ARTreeWatch on two types of smartphones equipped with different cameras and inertial measurement units (IMUs) to capture the three-dimensional (3D) point clouds and measure the TH and DBH of 51 trees in three plots with different tree species compositions. When the two types of smartphone measurements were compared with traditional ground surveys, the root mean square error (RMSE) of the estimated DBH ranged from 1.04 cm to 1.21 cm, and the RMSE of the TH ranged from 1.29 m to 1.98 m. Meanwhile, half the labor costs and time were saved compared to traditional field surveys. ARTreeWatch is an efficient, accurate, and lower-cost solution for measuring the structural parameters of trees in urban environments, which may be useful to urban landscape managers and researchers.