This study reports on a low-cost unmanned aerial vehicle (UAV)-borne light detection and ranging (LiDAR) system called LasUAV, from hardware selection and integration to the generation of three-dimensional point clouds, and an assessment of its performance. Measurement uncertainties were estimated in angular static, angular dynamic, and real flight conditions. The results of these experiments indicate that the point cloud elevation accuracy in the case of angular static acquisition was 3.8 cm, and increased to 3.9 cm in angular dynamic acquisition. In-flight data were acquired over a target surveyed by nine single passages in different flight directions and platform orientations. In this case, the uncertainty of elevation ranged between 5.1 cm and 9.8 cm for each single passage. The combined elevation uncertainty in the case of multiple passages (i.e., the combination of one to nine passages from the set of nine passages) ranged between 5 cm (one passage) and 16 cm (nine passages). The study demonstrates that the positioning device, i.e., the Global Navigation Satellite System real-time kinematic (GNSS RTK) receiver, is the sensor that mostly influences the system performance, followed by the attitude measurement device and the laser sensor. Consequently, strong efforts and greater economic investment should be devoted to GNSS RTK receivers in low-cost custom integrated systems. © 2018 by the authors.

Aim of study: To assess terrestrial laser scanning (TLS) accuracy in estimating biometrical forest parameters at plot-based level in order to replace manual survey for forest inventory purposes. Area of study: Monte Morello, Tuscany region, Italy. Materials and methods: In 14 plots (10 m radius) in dense Mediterranean mixed conifer forests, diameter at breast height (DBH) and height were measured in Summer 2016. Tree volume was computed using the second Italian National Forest Inventory (INFC II) equations. TLS data were acquired in the same plots and quantitative structure models (QSMs) were applied to TLS data to compute dendrometric parameters. Tree parameters measured in field survey, i.e. DBH, height, and computed volume, were compared to those resulting from TLS data processing. The effect of distance from the plot boundary in the accuracy of DBH, height and volume estimation from TLS data was tested. Main results: TLS-derived DBH showed a good correlation with the traditional forest inventory data (R²=0.98, RRMSE=7.81%), while tree height was less correlated with the traditional forest inventory data (R²=0.60, RRMSE=16.99%). Poor agreement was observed when comparing the volume from TLS data with volume estimated from the INFC II prediction equations. Research highlights: The study demonstrated that the application of QSM to plot-based terrestrial laser data generates errors in plots with high density of coniferous trees. A buffer zone of 5 m would help reduce the error of 35% and 42% respectively in height estimation for all trees and in volume estimation for broadleaved trees. © 2018 INIA.

Accurate estimates of tree biomass are strongly required for forest carbon budget estimates and to understand ecosystem dynamics for a sustainable management. Existing biomass equations for Mediterranean species are scarce, stand- and site-specific and therefore are not suitable for large scale application. In this study, biomass allometric equations were developed for stone pine (Pinus pinea L.), a Mediterranean tree species with relevant ecologic and economic interest. A dataset of 283 harvested trees was compiled with above- and belowground biomass from 16 sites in three countries (Italy, Spain, Portugal) representative of the species’ geographical Mediterranean distribution. A preliminary approach comparing the ordinary least squares method and the mixed model approach was performed in order to evaluate the most appropriate method for nested data in the absence of calibration data. To quantify the sources of error associated with applying biomass equations beyond the geographical range of the data used to develop them, a residual analysis was conducted. The allometric analysis showed low intra-specific variability in aboveground biomass relationships, which was relatively insensitive to the stand and site conditions. Significant differences were found for the crown components (needles and branches), which may be attributed to local geographical adaptation, site conditions and stand management. The root biomass was highly correlated with diameter at breast height irrespective of the geographical origin. Biased estimates were found when using site-specific equations outside the geographical range from where they were developed. The new biomass equations improved the accuracy of biomass estimates, particularly for the aboveground components of higher dimension trees and for the root component, being highly suitable for use in regional and national biomass forest calculations. It is, up to the present, the most complete database of harvested stone pine trees worldwide. © 2018