Tree-Level Multi-Sensor Assessment of Soil-Related Canopy Structural Variability in a Mandarin Orchard

Soil spatial variability is a key driver of tree development in perennial crops, and its characterisation is essential for precision orchard management. Against this background, soil–canopy relationships were investigated in a Citrus reticulata Blanco cv. Tango orchard under Mediterranean conditions. Electromagnetic induction (EMI), unmanned aerial vehicle (UAV) multispectral imagery, and mobile LiDAR data registered using a Simultaneous Localisation and Mapping (SLAM) workflow were integrated at individual-tree level. A previously validated EMI-derived apparent electrical conductivity (ECa) layer was used as a baseline descriptor of soil variability. UAV and mobile LiDAR acquisitions were harmonised for 40 trees: LiDAR point clouds were voxelised to derive canopy structural traits, while UAV imagery provided Soil-Adjusted Vegetation Index (SAVI) values. ECa at 14 kHz was negatively correlated with canopy volume (r = −0.605, R2 = 0.365) and canopy volume-to-projected area ratio (r = −0.571, R2 = 0.326), both significant at p < 0.001. Conversely, SAVI showed a weaker, non-significant relationship with ECa (r = −0.285, R2 = 0.081, p = 0.0749). The reduced multiple linear regression model explained canopy volume variability (R2 = 0.804), retaining canopy diameter and ECa as significant predictors. These findings highlight the value of LiDAR-derived structural traits as sensitive indicators of soil-related canopy variability, supporting the integration of structural, spectral, and soil-sensing data for site-specific orchard management.