Exploratory Analyses of Cross-Species Phenological–Structural Relationships in Urban Park Trees by Using Sentinel-2 Images and Handheld LiDAR Data

Understanding the interplay between tree structure and seasonal dynamics, particularly cross-species, is crucial for managing urban forest ecosystems. However, balancing fine-scale inventory of trees with large-area mapping of forest ecosystems is a challenge. This endeavor integrates multi-temporal Sentinel-2 satellite remote sensing (RS) imagery with high-density handheld light detection and ranging (LiDAR) point clouds to launch exploratory analyses of cross-species phenological–structural relationships (CSPSRs) in urban park trees. We derived plot-level phenological metrics (e.g., start of growing season, SOS) and quantified fine-scale three-dimensional (3D) tree structural attributes (e.g., tree height and trunk curvature), respectively. Then, we investigated how the 3D structural attributes of urban park trees covary with their phenological traits. The results revealed the underlying CSPSRs, e.g., a weak but significant negative correlation between SOS and tree height in the study area. The derived CSPSRs demonstrate that tree structure is a key predictor of its phenology, even across species. Overall, the integrated RS approach can provide a robust framework for associating the structure and phenology of trees, offering valuable insights for the ecological management of urban forests.