Development of mobile application for tree height measurement using geometric principle: Establishing global database of tree height and data

Accurate measurement of tree height is essential for ecological research, forest management, and carbon sequestration assessments. Traditional tools such as clinometers often face limitations due to terrain complexity, tree species variability, and operator dependency, while advanced technologies like LiDAR and UAVs, though precise, remain costly and less accessible. In this study, we developed a photographic tree height measurement method and integrated it into an Android application, referred to as M-Tree. The app allows users to capture tree images and calculate height using pixel-based markers, with the results synced to a global database containing tree height and associated data. To validate accuracy, M-Tree's measurements were compared to those obtained using a Suunto clinometer across 85 samples of trees and non-tree objects. Validation through Pearson correlation and Bland-Altman analyses demonstrated strong agreement, with root mean squared errors (RMSE) of 0.187 m for the clinometer and 0.192 m for M-Tree, alongside near-perfect correlations of 0.996 and 0.998, respectively. These results confirmed the M-Tree's effectiveness for tree height estimation, with a potential of broadening the geographic scope and accessibility of tree measurement data.