Work

Estimating the conversion factors for solid wood based on smartphone LiDAR in Thailand: a case study of high-value teak log piles in Thailand

Year: 2026

Type: article

Abstract: Accurate estimation of timber volume is critical for managing high-value teak (Tectona grandis) supply chains, yet traditional manual measurements remain laborious and prone to human error. This study evaluated the use of a low-cost, smartphone-integrated LiDAR sensor combined with freeware point-cloud processing to derive conversion factors between gross pile volume and solid wood content for teak roundwood in western Thailand. Forty heterogeneous log piles were scanned using an iPhone-based LiDAR system, and gross volumes were computed through 2.5D modelling in CloudCompare across progressively finer grid steps. Conversion factors were calculated using solid volumes provided by the Forest Industry Organisation. Mean absolute error analysis showed that conversion factor estimates stabilised at the finest grid step (0.001 m), demonstrating the reliability of the LiDAR-based workflow. Multiple linear regression revealed that log diameter, number of logs, and log length significantly influenced conversion factor variability (adjusted R2 = 0.54, p < 0.001), with diameter exerting the strongest effect. Average conversion factors ranged from 0.593 to 0.825, reflecting substantial variation in pile structure and log geometry. The findings highlight the feasibility of using low-cost LiDAR technology to provide objective, repeatable, and efficient volume estimates for teak log piles, offering a practical alternative to conventional measurement methods widely used in timber auctions. Further refinement incorporating detailed geometric attributes and broader validation across species and stacking conditions could enhance predictive accuracy and support the development of fully digitised roundwood inventory systems.

Source: Australian Forestry

DOI: 10.1080/00049158.2026.2718456

Authors: S. A. Borz, G. O. Forkuo, T. Kaakkurivaara, N. Kaakkurivaara

Institutions: Transylvania University of Brașov, Kasetsart University

Language: English

Topic: Remote Sensing and LiDAR Applications

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: hybrid

Funder: National Research Council of Thailand