Assessing forest parameters through the evaluation of smartphone-based measurement techniques

Abstract

The growing need for accessible and cost-effective methods in forest inventories has driven interest in utilizing smartphone-based technologies. This thesis examines the potential of six smartphone applications in assessing key forest parameters, namely tree height and diameter at breast height (DBH), and compares their performance against established methods such as terrestrial laser scanning (TLS) and manual measurements. The thesis is motivated by the demand for scalable, affordable, and user-friendly tools capable of supporting both professional forest management and citizen science initiatives.Field data were collected in a diverse forested area, where the selected applications were tested under real-world conditions to evaluate their measurement accuracy, usability, and efficiency. TLS and in-situ measurements using a measuring tape served as the reference for data validation, ensuring a robust benchmark for comparison. Particular attention was paid to identifying the strengths and limitations of the applications,including error sources related to environmental conditions and user experience. Furthermore, the thesis explored whether these smartphone-based solutions could achieve comparable or faster measurement times than traditional TLS methods while maintaining acceptable accuracy levels. Additionally, a simulation of errors was conducted to evaluate their detectability using real measurement data, offering recommendations for workflow adjustments to minimize errors.The results indicate that smartphone applications offer a promising alternative for forest inventories, particularly in scenarios where affordability and portability are critical. The average root mean square error (RMSE) across all tested applications was 2.3cm for DBH and 1.75 m for tree height, demonstrating a competitive level of accuracy.Notably, the maximal reduction of measurement errors for DBH for Geo-Quest was achieved when the tree occupied approximately 2/3 of the smartphone screen during measurement. The analysis also highlighted opportunities for optimization in application design, including the integration of advanced error correction algorithms and more intuitive user interfaces.This research contributes to the growing body of knowledge on leveraging mobile technologies in forestry and provides practical recommendations for enhancing the reliability and efficiency of smartphone-based measurement tools. By bridging the gap between professional-grade equipment and accessible technologies, this thesis underscores the potential of smartphones to democratize forest data collection and foster greater public engagement in environmental monitoring.