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The aim of this paper is to achieve a quantitative assessment of rockfall protection forest efficiency at regional scale, considering site specific forest, morphological and lithological parameters. At first, a semi-automatic GIS-based method, integrated with a multi-scenario 3D-rockfall model realized by using the simulation code HY-STONE, was used to map protection forests of Regione Lombardia (central Italian Alps). For each different forest type, a rockfall protective efficiency was assessed by using empirical (energy line angle) and modelling (HY-STONE) approaches. The empirical approach shows an increase of the energy line angle value from about 36° for the bare slopes to over 40° in forested slopes, with a value ranging from 37° to 44° for different forests types. The modelling approach is based on a new efficiency index EEI ranging from 0 (minimum efficiency, equal to no forest condition) to 1 (maximum efficiency): the efficiency of different forest types ranges from 0.08 to 0.98 by using average values of the controlling parameters. To modulate the efficiency in each single forest at regional scale, a set of parametric simulations was performed to evaluate the effects of controlling parameters. The parametric simulations show that block volume, slope gradient, DBH (diameter at breast height) and forest density are the most important parameters at controlling the efficiency. These parameters were used within a multiple linear regression function to associate a protection efficiency to each specific protection forest in the regional map. This allows to discriminate quantitatively the individual forests according to their actual efficiency. Most of the protection forest area (46%) shows an efficiency greater than 0.50 and only the 24% of the total covered area shows a value lower than 0.25.

Large landslides and deep-seated gravitational slope deformations (DSGSD) represent an important geo-hazard in relation to the deformation of large structures and infrastructures and to the associated secondary landslides. DSGSD movements, although slow (from a few millimetres to several centimetres per year), can continue for very long periods, producing large cumulative displacements and undergoing partial or complete reactivation. Therefore, it is important to map the activity of such phenomena at a regional scale. Ground surface displacements at DSGSD typically range close to the detection limit of monitoring equipment but are suitable for synthetic aperture radar (SAR) interferometry. In this paper, permanent scatterers (PSInSAR™) and SqueeSAR™ techniques are used to analyse theactivity of 133 DSGSD, in the Central Italian Alps. Statistical indicators for assigning a degree of activity to slope movements from displacement rates are discussed together with methods for analysing the movement and activity distribution within each landslide. In order to assess if a landslide is active or not, with a certain degree of reliability, three indicators are considered as optimal: the mean displacement rate, the activity index (ratio of active PS, displacement rate larger than standard deviation, overall PS) and the nearest neighbor ratio, which allows to describe the degree of clustering of the PS data. According to these criteria, 66% of the phenomena are classified as active in the monitored period 1992–2009. Finally, a new methodology for the use of SAR interferometry data to attain a classification of landslide kinematic behaviour is presented. This methodology is based on the interpretation of longitudinal ground surface displacement rate profiles in the light of numerical simulations of simplified failure geometries. The most common kinematic behaviour is rotational, amounting to 41 DSGSDs, corresponding to the 62.1% of the active phenomena.

This study shows a quantitative rockfall risk assessment (QRA) for a slope of the Feifeng Mountain (China), including an explicit assessment of the uncertainties. For rockfall risk analysis, the annual probability of occurrence, reach probability, temporal–spatial probability and vulnerability of tourists were calculated for both dry and rainy day conditions. The resulting individual risk for exposed people visiting the historical site can be considered as acceptable for all scenarios, whereas the overall societal risk lies within the as low as reasonably practicable (ALARP) zone and therefore requires some mitigation actions. For the explicit assessment of uncertainty, an error propagation technique (first-order second moment (FOSM)) was adopted, starting from expert knowledge heuristic estimations of the coefficient of variation for each component of the risk analysis procedure. As a result, coefficients of variation of the calculated risk were obtained, ranging from 48 to 132 %, thus demonstrating the importance of accounting for uncertainty in rockfall risk modelling. A multi-criteria methodology is also proposed for the assessment of the standard deviation of the parameters adopted for the stochastic rockfall run-out model.