Root system architecture (RSA) refers to the geometric features and topology of the root system. Ground-penetrating radar (GPR) is a possible method of RSA reconstruction. However, because the topology of the root system is not directly accessible by GPR, GPR-based reconstruction must be complemented by manual connection of root points, resulting in limited accuracy. In this study, we used both GPR and direct excavation to obtain 3D coordinates (XYZ coordinates) and diameters of moso bamboo rhizomes on an orthogonal grid. A score function for selecting the best-connected root points was developed using rhizome diameter, depth, extension angle, and measured line spacing, which was then used to recover the topology of discrete root points. Based on the recovered topology, the 3D RSA of the rhizomes was reconstructed using a smoothing function. Based on the excavation data, the reconstructed RSA was generally consistent with the measured RSA, with 78.13% of root points correctly connected. The reconstructed RSA based on GPR data thus provided a rough approximation of the measured RSA, with errors arising due to missing root points and rhizome displacement. The proposed algorithm for reconstructing 3D RSA further enriches the application of ground-penetrating radar to root detection.

The canopy is the direct receiver and receptor of external environmental variations, and affects the microclimate and energy exchange between the understory and external environment. After autumn leaf fall, the canopy structure of different forests shows remarkable variation, causes changes in the microclimate and is essential for understory vegetation growth. Moreover, the microclimate is influenced by the scale effect of the canopy. However, the difference in influence between different forests remains unclear on a small scale. In this study, we aimed to analyze the influence of the scale effect of canopy projection on understory microclimate in three subtropical broad-leaved forests. Three urban forests: evergreen broad-leaved forest (EBF), deciduous broad-leaved forest (DBF), and mixed evergreen and deciduous broad-leaved forest (MBF) were selected for this study. Sensors for environmental monitoring were used to capture the microclimate data (temperature (T), relative humidity (RH), and light intensity (LI)) for each forest. Terrestrial laser scanning was employed to obtain the canopy projection intensity (CPI) at each sensor location. The results indicate that the influence range of canopy projection on the microclimate was different from stand to stand (5.5, 5, and 3 m). Moreover, there was a strong negative correlation between T and RH, and the time for T and LI to reach a significant correlation in different urban forests was different, as well as the time for RH and LI during the day. Finally, the correlation between CPI and the microclimate showed that canopy projection had the greatest effect on T and RH in MBF, followed by DBF and EBF. In conclusion, our findings confirm that canopy projection can significantly affect understory microclimate. This study provides a reference for the conservation of environmentally sensitive organisms for urban forest management.