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

Natural resources management requires several parameters estimate in order to support the identification of the best alternatives to forest areas management. In particular, forest ecosystems require a complex and increasing set of descriptive information, where forest inventories put up important information, however not in a continuous spatial way. Lately, several scientific researches have been focusing on establishing methodologies to relate data from field to those obtained from multispectral images. Modeling these relations can extend the estimates of forest inventory data to not sampled areas. This research evaluated performance of non-parametric analysis using the K-Nearest Neighbor (k-NN) on SPOT 5 images. It evaluated the results obtained from the spatialization of some forest attributes in a forest area located at Molise, Italy. Among several methodologies for spatial distance calculations, the use of multiregressive non-parametric distances revealed the best results. Density and number of species on the ground revealed a Pearson correlation coefficient of = 0.58 as compared to data obtained from multispectral images, lightly lower than the obtained for basal area and volume, which were = 0.62 and 0.71, respectively.