Accurate in situ estimates of leaf area index (LAI) are essential for a wide range of ecological studies and applications. Due to the destructiveness and impracticality of direct measurements, indirect optical methods have mostly been used in the field to derive estimates of LAI from gap fraction measurements. Terrestrial laser scanning (TLS) is strongly supporting use of this active technology, which possesses several advantages compared to passive sensors. However, edge effects and partial beam interceptions are significantly challenges for the accurate retrieval of gap fraction from 3D point cloud data available from TLS, particularly in phase-shift instruments, which in turns require point cloud filtering to correct erroneous point measurements. As the limitations above influences the point cloud, we proposed a new method which is based only on the laser return intensity (LRI) information derived from raw TLS data, which are used to generate 2D intensity images. The intensity image contains all the unfiltered LRI information captured by TLS, which is used to separate gap from non-gap pixels, using a procedure comparable to the standard image analysis processing of digital hemispherical images. This allows a theoretically consistent comparison between active and passive optical measurements of gap fraction across all the zenith angle range. The method was tested in real and simulated forests. Gap fraction, canopy openness and effective leaf area index derived from real and simulated intensity TLS images were compared with those obtained using digital hemispherical photography (DHP). Results indicated that the intensity, image-based method outperformed DHP, as the higher pixel resolution of the intensity images and the larger distance covered by TLS allowed detection of many small canopy elements, particularly at higher zenith angles (longer optical distance), which are not detected in DHP. The main findings support the reliability of the intensity, image-based method to standardize protocols for TLS phase-shift scan data processing and use of the produced canopy estimates as a benchmark for passive optical measurements. © 2019 Elsevier B.V.

The "Bosco Fontana" natural reserve includes the last remaining mixed floodplain forest in northern Italy and one of the most endangered ecosystems in Europe. Its effective management is hindered by the complexity of interactions of mixed-tree species and the influence of environmental factors on understory plant diversity. In this study we analyzed the patterns of natural evolution in semi-natural floodplain forest stands at Bosco Fontana with the aim of better understanding its current natural processes and dynamics. Stand structure, taxonomic and functional diversity, species composition, and leaf area index (LAI) of overstory and understory layers were surveyed in permanent plots over two inventory years (1995, 2005). The influence of environmental factors on understory plant diversity was assessed using Ellenberg’s indices for light, soil moisture, soil nutrient and soil reaction. Results indicated that overstory species composition varies according to the soil moisture, with hornbeam prevailing in xeric sites and deciduous oak species in mesic sites. Xeric sites showed high functional dispersion in both drought and shade tolerant traits, while it was significantly lower in both overstory and understory in the moist site. Functional dispersion of drought tolerance in the overstory and understory layers was positively correlated, while species richness was negatively correlated between the two layers. Diversity in the understory was mainly correlated with soil conditions. Understory LAI was positively correlated with overstory LAI in xeric and mesic plots, while no correlations were found in the moist plot. Overall, our results suggest that site conditions (soil conditions and water availability) are the major drivers of understory and overstory dynamics in the study forest. Hence, local site conditions and the understory should be carefully considered in the management of mixed floodplain forests. © SISEF.