| Issue |
BIO Web Conf.
Volume 194, 2025
International Scientific Conference on Biotechnology and Food Technology (BFT-2025)
|
|
|---|---|---|
| Article Number | 01073 | |
| Number of page(s) | 7 | |
| DOI | https://doi.org/10.1051/bioconf/202519401073 | |
| Published online | 14 November 2025 | |
Smartphone-based measurements of Scots pine trunk diameters in Kostroma region, Russia
Russian State Agrarian University - Moscow Timiryazev Agricultural Academy, 49, Timiryazevskaya st., 127434 Moscow, Russia
1 Corresponding author: d.gosteva@rgau-msha.ru
In the study, the use of a smartphone equipped with a LiDAR sensor for forest stand inventory was analyzed. The accuracy of determining diameter at breast height (DBH), basal area, and stand volume was investigated by comparing the Arboreal Forest app with traditional forest inventory methods. Data from pure Scots pine stands across four temporary sample plots in the Kostroma region (Russia) were examined. Metrics such as RMSE, MBE, MAE, MAPE, and R² were determined based on statistical analysis and graphical evaluations. A high agreement between DBH and basal area values obtained via the Arboreal Forest app and manual caliper measurements was established, with mean DBH deviations not exceeding ±1.6%. The alignment of diameter class distributions, confirmed by the Kolmogorov-Smirnov test ( p = 0.05), was validated across all plots. Permissible deviations in stand basal area and volume (±3.2%) were identified, meeting Russian forest inventory standards. Directions for improving mobile LiDAR-based technologies to enhance forest assessment efficiency were proposed. The potential for scaling this methodology to other forest types was substantiated. Overall, the results demonstrate smartphones’ viability as rapid, accurate tools for forest inventory, maintaining compliance with regulatory precision requirements.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

