Teleoperated Quadruped Robot-Based SLAM LiDAR for Standardized Tree Stem Diameter Derivation in Spanish Mediterranean Savanna-like Woodlands: A Field Feasibility Study

Mediterranean Dehesa woodlands require monitoring of tree structural change, but conventional stem-diameter inventories are labor-intensive. Mobile simultaneous localization and mapping (SLAM) LiDAR can acquire three-dimensional tree structure, although inconsistent trajectories and uneven stem coverage may reduce measurement repeatability. This study evaluated whether a teleoperated quadruped carrying a Hovermap ST sensor along standardized circular trajectories could acquire stem-level point clouds suitable for diameter-at-breast-height (DBH) estimation in open Dehesa terrain. Backpack-mounted surveys were conducted in 2025 at Majadas de Tiétar, followed by quadruped-mounted surveys in 2026 at two Spanish sites. DBH was derived from horizontal slices at 1.3 m using Circle Fitting, Convex Hull Peeling, and Kalman-filter reconstruction, then compared with height-matched manual references. Backpack estimates for 186 caliper-referenced observations achieved R2 values of 0.853–0.869, Lin’s concordance coefficients of 0.787–0.833, and root-mean-square errors of 5.22–6.11 cm. After excluding one bifurcation-affected observation, 29 robot estimates achieved R2 values of 0.930–0.943, concordance coefficients of 0.941–0.956, and root-mean-square errors of 3.17–3.84 cm. Robot acquisitions showed more balanced radial point distributions and fewer reconstruction errors. However, dataset differences preclude controlled platform comparison. Quadruped-mounted SLAM LiDAR therefore shows promise for standardized one-time DBH inventories, while paired same-tree repeatability studies remain necessary before application to multitemporal growth monitoring.