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Abstract
Objective: To evaluate the accuracy of the iPhone 15 Pro® LiDAR sensor for measuring diameter at breast height (DBH) and photogrammetry with unmanned aerial vehicle (UAV) for estimating tree height.
Methodology: The research was conducted in a 17-year-old mixed plantation. DBH was measured with a diameter tape, and tree height with a clinometer. These measurements were compared with data from the LiDAR sensor and UAV photogrammetry. Agreement was assessed using linear regression (R², RMSE) and the intraclass correlation coefficient (ICC).
Results: High agreement was observed between traditional methods and remote sensing. For DBH, the comparison yielded R² = 0.95, RMSE = 1.47 cm, and ICC = 0.964. For height, the results showed R² = 0.96, RMSE = 0.64 m, and ICC = 0.981.
Study limitations/implications: The study was conducted in a plantation with regular spacing. The results should be validated under different conditions (species and stand structures). The slight systematic underestimation of DBH using LiDAR, attributed to the sensor's resolution, justifies its operational use.
Findings/conclusions: Remote sensors provided accuracy comparable to that of traditional techniques, with superior operational efficiency. iPhone LiDAR is viable for DBH measurement, and UAV photogrammetry is suitable for height estimation in commercial inventories. Their integration allows for automated, georeferenced digital databases for advanced spatial analysis.