A low-cost wireless dendrometer and digital twin for precision forestry applications

Scalable, continuous monitoring of tree stem radial dynamics is a prerequisite for quantifying individual-tree water status and growth responses to environmental stress, yet the cost and logger-dependency of commercial point dendrometers have prevented deployment beyond small research plots. Addressing this gap requires not only affordable hardware, but a principled framework for characterising measurement uncertainty — a standard rarely applied to low-cost ecological sensors. This study presents the development, metrological characterisation, and field validation of an open-hardware, logger-free dendrometer and environmental sensing node with integrated LoRaWAN telemetry. A physics-based digital twin was developed alongside the hardware to decompose the instrument error budget into its mechanical, thermal, and electronic contributions, enabling uncertainty to be quantified and attributed prior to deployment. The device achieves an effective displacement resolution of 0 . 0763 μ m and post-calibration accuracy within tens of micrometres of a micrometre reference standard; bracket thermal expansion was identified as the dominant drift source, with a system thermal coefficient of approximately − 1 to − 1 . 5 μ m ∘ C − 1 . Monte Carlo simulation confirmed that device-specific polynomial calibration eliminates systematic bias, reducing mean RMSE to 69 μ m across simulated component variability. Field deployment on two Eucalyptus species across climatically contrasting sites in South Africa and Portugal resolved ecophysiologically meaningful contrasts in radial growth, tree water deficit, and maximum daily shrinkage coupled to vapour pressure deficit and soil water availability. LoRaWAN telemetry was confirmed at 3 . 4 km under rural conditions within network fair-use constraints. These results demonstrate that rigorous, wireless dendrometry is achievable at a cost and scale accessible to precision forestry, drought-stress monitoring, and large-scale tree ecophysiology research.