Search

Models of stand volume and biomass estimation based on LiDAR data for the main forest types in Calabria (southern Italy). The AlForLab project is part of the Cluster MEA (Materials Energy Environment) addressed to the Calabria Region. Estimating the main dendrometric variables of Calabrian forests using models based on publicly available remote sensed data is one of the main purposes of the project. This paper describes the procedures used to develop several thematic maps (raster and vector) of timber volume and phytomass to be used in planning and management activities at both regional and forest property scale, as well as for felling plans, logging projects etc. We used public LiDAR data at medium-low resolution (1.6 pts m-2), acquired on about 90% of Calabrian territory in the frame of a national remote sensing programme of the Italian Ministry of the Environment. Field data from the second National Forest Inventory (INFC 2005) on 311 sample points were used for model calibration, as well as new field data acquired specifically for AlForLab project on 143 angle count samples. A series of regression models to predict volume and its corresponding aboveground biomass (dry and fresh weight) were developed and digital maps at different spatial resolutions were produced, as well as their estimate uncertainties. These models and their mapping products are also an important part of the new-establishing forest Decision Support System CFOR. The adopted models, though based on the same mathematical equation, have specific coefficients for different species and groups of species, according to a forest type classification system compatible with the fourth level of Corine Land Cover. In this way it is possible to apply the models without accessing more detailed forest type maps. All estimation methods and procedures are consistent with national forest inventory models, and with the other new tools proposed by AlForLab project to estimate timber volume, such as the regional tariffs and the field sampling inventory procedures. R2 adjusted values (for models at the highest typological detail) are between 60% and 85%, whereas uncertainties of timber volume estimate (ESS%) range from 25% (for main forest species) up to 50% (for less spread forest types). All processing steps to produce digital maps were performed on open-source environment (R and QGIS).

In this work, a spatial decision support system dedicated to forest management in Calabria (CFOR) is presented. The main aim of the tool is to assess wood production under various harvesting options. All functionalities have been developed by Python and R languages for QGIS. Main inputs are digital models, mainly derived from Lidar, and vector shapefiles.

Recently, the Society’s perception of forest resources has gone through significant changes. Forest ecosystems play a multifunctional role and host an important portion of the whole biodiversity, particularly in the Mediterranean area. Remote sensing technologies provide a unique way to obtain spatially extensive information on forest ecosystems, but relatively few studies used such information to evaluate forest habitat and biotic diversity. In this paper we evaluate the effectiveness of remote sensing to predict forest diversity by linking remotely sensed information with diversity metrics obtained from ground measurements of butterfly diversity. The field work was carried out in Calabria in four different forest types (beech, chestnut, black pine and silver fir forests). The sampling of Lepidoptera was carried out by LED light traps. We positioned 9 traps per forest type, for a total of 36 sites chosen to sample the different stages of forest succession in each forest type. Samples were carried out once a month from May to November 2015. Data from in situ butterfly measurements were compared with above ground forest biomass estimated from airborne LiDAR with NDVI estimated from Landsat 8. Results indicated that the Geometridae/Noctuideae ratio of lepidopteran communities was significantly correlated with the tree biomass, its distribution among tree size classes and the NDVI. The Geometridae/Noctuidae ratio, therefore, represents an index easy to calculate, which can be employed to integrate data acquired from remote sensing in order to obtain continuous spatial estimates of forest naturalness.

Recent advancements in informatics and communication technologies have led to an increasing employment of analytical and communication tools in forestry, including data from satellite, airborne, unmanned aerial vehichles, global positioning systems, and many sensors, devices and other geospatial tools. Precision forestry enables highly repeatable measurements, actions and processes to manage and harvest forest stands, simultaneously allowing information linkages between production and wood supply chain, involving resource managers and environmental community; all these factors are contributing to the wider goal of sustainable forest management. In this report, we review the most recent advances in the precision forestry applications and tools, with particular reference on advanced forest inventory, decision support systems, precision forest harvesting, and wood traceability. We discuss the opportunities and challenges towards implementing precision forest practices in forest management and planning and forest industry in Italy.

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.

Proximal sensing methods using digital photography have gained wide acceptance for describing and quantifying canopy properties. Digital hemispherical photography (DHP) is the most widely used photographic technique for canopy description. However, the main drawbacks of DHP have been the tedious and time-consuming image processing required and the sensitivity of the results to the image analysis methods. Recently, an alternative approach using vertical photography has been proposed, namely, digital cover photography (DCP). The method captures detailed vertical canopy gaps and performs canopy analysis by dividing gap fractions into large between-crown gaps and small within- crown gaps. Although DCP is a rapid, simple and readily available method, the processing steps involved in gap fraction analysis have a large subjective component by default. In this contribution, we propose an alternative simple, more objective and easily implemented procedure to perform gap fraction analysis of DCP images. We compared the performance of the two image analysis methods in dense deciduous forests. Leaf area index (LAI) estimates from the two image analysis methods were compared with reference LAI measurements obtained through the use of litter traps to measure leaf fall. Both methods provided accurate estimates of the total gap fraction and, thus, accurate estimates of the LAI. The new proposed procedure is recommended for dense canopies because the subjective classification of large gaps is most error-prone in stands with dense canopy cover.

Tree biomass plays a key role in sustainable forest management and in determining forest carbon stocks. Accurate estimates based on species-specific empirical data are necessary for regional and national inventories and forest carbon management. In this study, we obtained allometric relationships for volume and aboveground biomass for stone pine (Pinus pinea) based on empirical data collected in four coastal stands in Italy. Root sampling was also performed. The results enabled generalized equations for volume and aboveground biomass to be developed. However, an analysis also showed several differences in biomass allocation in stone pine resulting from different stand characteristics, emphasizing the importance of stand-dependent factors for adjusting regional or national biomass calculations. Biomass expansion factors were also provided. This study provides tools to help forest managers in quantifying volume and biomass, thereby contributing to the accurate estimation of carbon sequestration and stocks in stone pine stands in Italy.

Hemispherical photography has been used since the 1960s in forest ecology. Nevertheless, specific constraints related to film cameras have progressively prevented widespread adoption of this photographic method. Advances in digital photographic technology hold great promise to overcome the major drawbacks of hemispherical photography, particularly regarding field techniques and image processing aspects. This contribution is aimed to: (i) provide a basic foreground of digital hemispherical photography; (ii) illustrate the major strengths and weakness of the method; (iii) provide an reliable protocol for image acquisition and analysis, to get the most out of using hemispherical photography for canopy properties extraction.