1,720,995 research outputs found
A detailed description of flowering stages in olive tree in relation to side tree crown exposure
No full textAnalisi di correlazione degli impatti delle attività turistiche nel territorio di Alghero
No full textAnalysis of phenological behaviour of some mediterranean Shrub species in responses to warming and drought conditions
No full textA phenological behavior of Mediterranean species growing in a Mediterranean-type climate was described by developing a phenological scale. The sensitivity of some Mediterranean species to climate manipulations was evaluated. Climate manipulations were conducted on a Mediterranean macchia ecosystem that include sclerophyll species. The increase of daily minimum temperature of air and soil observed at 20 cm height and at 10 cm depth in the warming treatment was approximately equal to 0.5°C relative to control
Analisi della distribuzione spaziale della vegetazione: un esempio di applicazione alla macchia mediterranea nella penisola di Capo Caccia (Sassari)
No full textPollen emission from olive trees and concentrations of airborne pollen in an urban area of North Sardinia
No full textIn this study the seasonal and daily variations in olive airborne pollen concentrations were measured in-the atmosphere of Sassari (Italy) and the olive pollen emission was monitored in the countryside during the flowering period in 1995 and 1996, in order to detect the patterns of change in the atmosphere. The intensity and the timing of pollination was also studied in relation to phenological stages occurrence. In addition, the influence of the main meteorological parameters on pollen emission and airborne pollen dispersal in the city was assessed. Airborne pollen reached its highest concentration a few days before the peak of pollen emission in 1995 but several days after it in 1996 (6 days). Analysis of hourly concentrations shows that the maximum emission and dispersion recorded during the observation period occurred in the middle of the day. Significant regressions were found between hourly temperature and air humidity values and hourly pollen concentrations recorded in the olive grove for almost every day studied, indicating a negative correlation between humidity and pollen concentration and a positive correlation between pollen concentration and temperature. On the other hand, no significant correlation was observed between the meteorological parameters and pollen concentration recorded in the urban area
Using terrestrial LiDAR for monitoring canopy structure in cork oak trees
No full textThe main aim of this work was to assess the capabilities of terrestrial laser scanner in measuring both changes by the time and differences among trees of canopy characteristics ofQuercus suberL. (cork oak) plants
Modelling wildfire activity in wildland–urban interface (WUI) areas of Sardinia, Italy
Full text linkBackground. Wildfire frequency, magnitude and impacts in wildland–urban interface (WUI) areas are increasing in the Mediterranean Basin. Aims. We investigated the role played by socioeconomic, vegetation, climatic, and zootechnical drivers on WUI wildfire patterns (area burned and wildfire ignitions) in Sardinia, Italy. Methods. We defined WUI as the 100-m buffer area of the anthropic layers. We created a comprehensive and multi-year dataset of explanatory variables and wildfires, and then trained a set of models and evaluated their performances in predicting WUI fires. We used the best models to assess the single variable’s importance and map wildfire patterns. Key results. Random Forest and Support Vector Machine were the best performing models. In broad terms, wildfire patterns at WUI were influenced by socio-economic factors and herbaceous vegetation types. Conclusions. Machine learning models can be useful tools to predict wildfire ignitions and area burned at WUI in Mediterranean areas. Implications. Improved knowledge of the main drivers of wildfires at WUI in fire-prone Mediterranean areas can foster the development or optimisation of wildfire risk reduction and prevention strategies
An automated approach for wood-leaf separation from terrestrial LIDAR point clouds using the density based clustering algorithm DBSCAN
No full textThe terrestrial light detection and ranging (LiDAR) technique has been recently used to provide 3D structural information of forest canopy at the individual tree level. However, the operational use of Terrestrial Laser Scanner (TLS) for canopy characterization of broadleaf non-deciduous forests needs further investigations. The estimation of wood volume, above-ground woody biomass, tree canopy characteristics and leaf area index often requires separation of photosynthetically active material and non-photosynthetically active material. This article describes an automated wood-leaves separation method, based on spatial geometric information of TLS point clouds, for broad leaved non-deciduous trees. Scans of seven individuals of Quercus suber L. trees were acquired by using the TLS phase-based Leica HDS6100. Point clouds were partitioned in cubic volumes (voxels) that were used as input to generate clusters through the point density algorithm DBSCAN. The clustering process led to the identification of wood and non-wood voxels. A specific automatic routine was written to process data from the point clouds to the visualization of clustering results. The analysis of results showed good performance for this approach, with the overall accuracy in classifying wood components of trees ranging from 95% to 97%. The largest accuracies were observed for branches larger than 5 cm in diameter whereas the accuracy of classification dropped, as expected, for branches with diameter lower than 3 cm. The results suggest that the proposed method can be conveniently used to extract woody components from point clouds of broad leaved non-deciduous trees
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