Vegetation structure is one of the key factors in forest ecosystems. Especially understory structure has major implications for wildlife habitat selection, reproduction, and survival. Structural indices traditionally used to characterize understory vegetation are based on field vegetation surveys describing general features such as leaf area index (LAI), canopy cover or vegetation height, hiding much of the three-dimensional vegetation structure complexity. The application of terrestrial laser scanning (TLS) in forest ecological and management applications is becoming more effective. In this study, we use TLS data to quantify spatial attributes of forest subcanopy in four different forest strata ranging from 0.5 m to 10 m from the ground. We collected data in 12 plots of mature European beech (Fagus sylvatica L.) forests and 12 plots of mature black pine (Pinus nigra subsp. laricio Maire) forests, located in the Sila National Park, Italy. We propose a TLS-based approach to estimate a fine-scale vegetation density using the Plant Density Index (PDI) and to test the PDI at different height classes. We found a significant relationship between the PDI and the number of trees belonging to the dominant layer, using the Spearman correlation coefficient (r = 0.83, p<inf>val</inf> = 0.001). Basing on PDI values, a cluster analysis of the four subcanopy strata was carried out for deriving clusters of structurally homogeneous forest plots. Results identified three clusters in terms of the vegetation features in the horizontal height classes: the first cluster primarily includes Beech forests characterized by plots with the highest tree densities; the second one includes both Beech and Pine forests characterized by dense ground vegetation and shrubs and an intermediate tree density; the third group is represented by Pine forests with massive presence of vegetation lower strata and moderate tree density. Then, PCA allowed identifying the relationship between the considered subcanopy layers and forest plots. © 2021 Elsevier B.V.

Vegetation structure is a key determinant of species distribution and diversity. Compared to traditional methods, the use of Terrestrial Laser Scanning (TLS) has allowed massive amounts of point cloud data collected for quantifying three-dimensional habitat properties at increasing spatial and temporal scales. We used TLS to characterize the forest plots across a broad range of forest structural diversity, located in the Sila National Park, South Italy. The dataset reports data collected in 24 15-m-radius circular plots, 12 of which were dominated by beech (Fagus sylvatica L.) and 12, by black pine (Pinus nigra subsp. laricio). In detail, this work provides dataset of i) plot-level attributes calculated from raw data, such as the number of trees, ii) tree-level data, comprising a total of 1709 trees, with information related to field-based forest inventory such as the diameter at breast height (DBH), and iii) plot-level information related to the time for conducting both traditional field- and TLS-based forest inventories. Compared to traditional methods, the use of TLS allows a very high-resolution quantification of the 3D forest structural properties, also reducing the time for conducting forest inventories. © 2020

Accurate estimates of crown cover (CC) are central for a wide range of forestry studies. As direct measurements do not exist to retrieve this variable in the field, CC is conventionally determined from optical measurements as the complement of gap fraction close to the zenith. As an alternative to passive optical measurements, active sensors like terrestrial Light Detection And Ranging (LiDAR) allows for characterizing the 3D canopy structure with unprecedented detail. We evaluated the reliability of terrestrial LiDAR (TLS) to estimate CC using a voxel-based approach. Specifically, we tested how different voxel sizes (ranging from 5-20 cm) and voxel densities (1-9 points/dm³) influenced the retrieval of CC. Results were compared against benchmark values obtained from digital cover photography (DCP). The trial was performed in hybrid poplar plantations in Northern Italy. Results indicate that TLS can be used for obtaining accurate estimates of CC, but the choice of voxel size and point density is critical for achieving such accuracy. In hybrid poplars, the best performance was obtained using voxel size of 10 cm and point density of 8 points/dm³. The combined ability of measuring and mapping CC also holds great potential to use TLS for calibrating and upscaling results using coarser-scale remotely sensed products. © 2021 Centro di Ricerca per la Selvicoltura, Consiglio per la Ricerca in Agricoltura e l'Analisi dell'Economia Agraria. All rights reserved.