Hybrid poplar plantations are essential for bioenergy, pulp and paper industries, and contribute to carbon sequestration and environmental restoration. Effective plantation management, including monitoring of canopy structure, is crucial to maximize productivity, but traditional inventory methods often lack the spatial and temporal resolution needed for precision forestry application. In this study, we evaluated use of continuous canopy photography for continuous monitoring of poplar plantations. Daily canopy attributes like foliage cover and leaf area index were derived from time-lapse trail cameras. Three poplar clones (Soligo, I-214, and Neva), having differing growth rates and drought tolerances, were tested under different water (irrigated vs non-irrigated) regimes. We demonstrated that continuous canopy attributes allow to quantify significant variations in canopy cover, associated with both clone type and water status. Non-irrigated trials exhibited early senescence and canopy decline, while irrigated clones showed more robust canopy development. We concluded that continuous cameras offer a low-cost, effective solution for improving hybrid poplar plantation management by timely tracking the ability to respond to varying environmental conditions and optimizing resource use. © 2025 Istituto Sperimentale per la Selvicoltura. All rights reserved.

The dataset reports data collected in 38 square (50 x 50m) 0.25 ha plots representative of poplar plantations in Lombardy Region (Northern Italy), which were used to calibrate optical information derived from unmanned aerial vehicle (UAV) and satellite (Sentinel-2) sensors. In each plot, the diameter at breast height was measured using a caliper; height, stem and crown volume of each tree were then derived from diameter using allometric equations developed in an independent study. Additional canopy attributes (foliage and crown cover, crown porosity, leaf area index) were derived in each plot from 12-20 optical images collected using digital cover photography (DCP). The collected data allows characterizing the assessment of structure of these plantations, along with their variation over the rotation time. Canopy and crown data also enable the evaluation of optimal rotation and tree spacing, as well as the relationship between stand and canopy structure. The raw datasets consist of 2,591 records (trees) associated with inventory measurements and 616 records (images) associated with optical canopy measurements. An R code was also provided to calculate plot-level attributes from raw data. Dataset and associated metadata are freely available at http://dx.doi.org/10.17632/ycr7w5pvkt.1. © 2021 Centro di Ricerca per la Selvicoltura, Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria. All rights reserved.