Impact of GEDI-Derived Forest Vertical Structure Characteristics on the Accuracy Gains in Regional Dominant Tree Species Mapping

Information about the composition and distribution of dominant tree species is crucial for sustainable forest management. A global ecosystem dynamics investigation (GEDI) offers unique advantages in detecting the vertical spatial structure of forest stands, which may improve the common issues of spectral similarity and saturation in traditional spectral-based tree species mapping. However, the effects of its application have not been explored. This study examines temperate and subtropical forests in eastern China, which are dominated by deciduous and evergreen species, respectively. We employed GEDI-derived forest vertical structure characterization (FVSC) to complement Sentinel-2 spectral features for dominant tree species mapping. The results indicate that FVSC significantly improved the mapping accuracy for 11 tree species in both temperate and subtropical forest regions across seasons, with greater benefits observed for broadleaf species than for coniferous species. During the main phenological stages of spring, summer, and autumn, the accuracy of tree species mapping in the temperate region improved by 6.99%–9.85%. The key contributing factors were the cumulative plant area index (PAI) from the ground to the canopy top and cumulative vegetation coverage (COVER) from 5 m to the canopy top. In the subtropical region, the accuracy improvement ranged from 7.75% to 9.5%, with the highest contributions from the plant gap probability (Pgap_theta) and cumulative COVER from 5 m to the canopy top. These findings demonstrate that FVSC can effectively support spectral feature data in the detailed mapping of dominant tree species at regional scales. Moreover, the method shows good stability and applicability across seasons and climatic regions.