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Pubblicazioni Scientifiche
Filtri di ricerca 5 risultati
Pubblicazioni per anno
Indicators for the assessment and certification of cork oak management sustainability in Italy
Pollastrini
,
M.
,
Chiavetta
,
U.
,
Cutini
,
Andrea
,
Casula
,
Antonio
,
Maltoni
,
Sara
,
Dettori
,
Sandro
,
Corona
,
P.
italy
forest management planning
non-wood forest products
quercus suber
sardinia
sustainable forest management
Mostra abstract
Sustainable forest management (SFM) is crucial for forest ecosystem productivity and conservation, especially in systems such as cork oak (Quercus suber L.) threatened by human activities and biotic and abiotic factors. In this study SFM indicators with particular reference to cork oak forests in the region of Sardinia (Italy) are proposed and tested. Sustainable and responsible management options specifically aimed at cork oak forest management and chain of custody certification are also provided. A set of ten indicators was proposed and assessed by an expert panel in cork oak management. Five indicators were also tested against data on structure, origin, health condition and management in 285 forest compartments managed by FoReSTAS (Regional Forest Agency for Land and Environment of Sardinia, Italy), including 361 sampling plots and 5345 trees. In order to investigate the priorities and perceptions of SFM experts and stakeholders, a survey was also carried out by completion of a questionnaire on the technical issues of cork oak woodland management. The survey results highlighted a need to improve environmental and economic performance by means of SFM and certification. The indicators tested in Sardinian cork oak woodlands showed that about 80% of the stands fulfilled management sustainability requirements. The suggested SFM indicators can effectively support proactive management and conservation measures, representing a valuable tool in the current context of growing environmental and socioeconomic awareness. © SISEF.
Development and performance assessment of a low-cost UAV laser scanner system (LasUAV)
Torresan
,
C.
,
Berton
,
Andrea
,
Carotenuto
,
Federico
,
Chiavetta
,
U.
,
Miglietta
,
F.
,
Zaldei
,
Alessandro
,
Gioli
,
Beniamino
lidar
forest monitoring
global navigation satellite system
real-time kinematics technology
system designing
system testing
Mostra abstract
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.
Generalized biomass equations for Stone pine (Pinus pinea L.) across the Mediterranean basin
Correia
,
A. C.
,
Faias
,
Sónia Pacheco
,
Ruiz-Peinado
,
Ricardo
,
Chianucci
,
Francesco
,
Cutini
,
Andrea
,
Fontes
,
Luís
,
Manetti
,
Maria Chiara
,
Montero
,
Gregorio
,
Soares
,
P.
,
Tomé
,
Margarida
aboveground biomass
allometry
carbon estimation
mixed models
residual analysis
root biomass
simultaneous fitting
Mostra abstract
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
Climate, tree masting and spatial behaviour in wild boar (Sus scrofa L.): insight from a long-term study
Bisi
,
Francesco
,
Chirichella
,
Roberta
,
Chianucci
,
Francesco
,
von Hardenberg
,
Jost Graf
,
Cutini
,
Andrea
,
Martinoli
,
Adriano
,
Apollonio
,
Marco
Mostra abstract
Key message: Climate factors affect seed biomass production which in turn influences autumn wild boar spatial behaviour. Adaptive management strategies require an understanding of both masting and its influence on the behaviour of pulsed resource consumers like wild boar. Context: Pulsed resources ecosystem could be strongly affected by climate. Disantangling the role of climate on mast seeding allow to understand a seed consumer spatial behaviour to design proper wildlife and forest management strategies. Aims: We investigated the relationship between mast seeding and climatic variables and we evaluated the influence of mast seeding on wild boar home range dynamics. Methods: We analysed mast seeding as seed biomass production of three broadleaf tree species (Fagus sylvatica L., Quercus cerris L., Castanea sativa Mill.) in the northern Apennines. Next, we explored which climatic variables affected tree masting patterns and finally we tested the effect of both climate and seed biomass production on wild boar home range size. Results: Seed biomass production is partially regulated by climate; high precipitation in spring of the current year positively affects seed biomass production while summer precipitation of previous year has an opposite effect. Wild boar home range size is negatively correlated to seed biomass production, and the climate only partially contributes to determine wild boar spatial behaviour. Conclusion: Climate factors influence mast seeding, and the negative correlation between wild boar home range and mast seeding should be taken into account for designing integrated, proactive hunting management. © 2018, INRA and Springer-Verlag France SAS, part of Springer Nature.
Estimation of ground canopy cover in agricultural crops using downward-looking photography
vegetation index
cie l*a*b*
fractional vegetation cover
gap fraction
green coordinates
nadir photography
Mostra abstract
Fast and accurate estimates of canopy cover are central for a wide range of agricultural applications and studies. Visual assessment is a traditionally employed method to estimate canopy cover in the field, but it is limited by the costs, subjectivity and non-reproducibility of the produced estimates. Digital photography is a low-cost alternative method. In this study we tested two automated image classification methods, the first one based on a histogram-analysis method (Rosin), the second one based on a combination of a visible vegetation index and the L*a*b* colour space conversion (LAB2), which have both been previously tested in forestry, and a supervised image classification method (Winscanopy), to estimate canopy cover from downward-looking images of agricultural crops. These methods were tested using artificial images with known cover; this allowed exploring the influence of canopy density and object size on canopy cover estimation from photography. The Rosin method provided the best estimates of canopy cover in artificial images, whose accuracy was largely unaffected by variation in canopy density and object size. By contrast, LAB2 systematically overestimated canopy cover, because of the sensitivity of the method to small variations of chromaticity in artificial images. Winscanopy showed good performance when at least two regions per class were manually selected from a representative image. The results were replicated in real images of cultivated aromatic crops. The main findings indicate that digital photography is an effective method to obtain rapid, robust and reproducible measures of canopy cover in downward-looking images of agricultural crops, including aromatic plants. © 2018 IAgrE