A precise forest spatial structure investigation using the SLAM+AR technology - Yan, Fei; Guan, Tianshuo; Ullah, Mohammad Rahmat; Gao, Li; Fan, Yongxiang (Frontiers in Ecology and Evolution, 2023)
Forest spatial structures are the foundations of structure and function of forest ecosystems. Quantitative descriptions and analysis of forest spatial structure have recently become common tools for digitalized forest management. Therefore, the accuracy and intelligence of acquiring the forest spatial structure information are of great significance. In this study, we developed a forest measurement system using mobile phone, and through this system the following tree measurements can be achieved: (1) point cloud of stumpage and chest diameter circle to measure tree diameter at breast height (DBH) and position coordinates of stumpage by using simultaneous localization and mapping (SLAM) technology, (2) virtual boundary creation of the sample plot and the auxiliary measurement function of stumpage with the augmented reality (AR) interactive module, , and (3) position coordinates and single wood factor data to calculate the spatial structural parameters of the forest (e.g., Mingling degree, Dominance index, Uniform angle index, and Crowdedness index). The system was tested in 32 × 32 m artificial mixed forest plots in where dominant tree species was Juniperus chinensis L. . The average DBH estimations showed a bias of 0.45 cm and a RMSE of 0.57 cm, and its accuracy level met the requirements of forestry sample survey. However, the tree position estimations were unbiased and had a RMSE of 0.21 m in the x-axis and 0.16 m in the y-axis. The spatial structural parameters of the sample forest area were as follows: the mingling degree of the forest area was 0.32, and the overall mixing degree of tree species was low; the dominance index was 0.56, and the overall situation was moderate; and the degree of competition was average; the Uniform angle index is 0.55; and the crowdedness index of the spatial structure was 1 which means that the trees in the forest area are randomly distributed. This study findings support for the optimization of forest structures and improve our conceptual understanding of forest community succession and restoration, in addition to the informatization and precision of forest spatial structure surveys.