The report describes a recent landslide occurred in San Leo (northern Italy), an outstanding village from the historical, architectural and landscape point of view. On February 27, 2014, around 6 pm local time, about 0.30 Mm3 of rock detached from a sub-vertical cliff and fell into the facing valley, producing a roar and a shake, which was initially perceived by the inhabitants as an earthquake, then followed by a dust cloud produced by the fragmentation of material during the collapse. Fortunately, nobody was injured, neither the landslide damaged any relevant structure; anyhow, it is still posing a severe threat to the village and, above all, to the fortress that represents an architectural masterpiece dating back to the middle ages. An outlook of the event will be given, along with the description of the peculiar geological and geomorphological features driving the slope instability phenomena, which indeed are widely diffused in the entire region. Lastly, an overview of the landslides, which historically affected the village, is also given, showing how natural hazards can influence the history of a site

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The stream length-gradient (SL) index is widely used in geomorphological studies aimed at detecting knickzones, which are extensive along-stream deviations from the typical concave-up shape assumed for stream longitudinal profiles at steady-state conditions. In particular, SL was practical for identifying anomalous gradients along bedrock stream channels in mountainous catchments. This work presents the GIS toolbox SLiX designed to extract values of the SL index, starting from Digital Elevation Models (DEMs). SLiX is also suitable for the spatial analysis of the SL values, allowing for the identification of landscape portions where anomalous high values of SL occur and, consequently, those catchment sectors where stream channels show peaks in the erosional dynamic. The SLiX main outputs are (i) point shapefiles containing, among stream channels attributes, the extracted values of SL along the stream network analyzed, and (ii) SL anomaly maps in GeoTIFF format, computed through the Hotspot and Cluster Analysis (HCA), that permit the detection of the catchment sectors where the major SL anomalies occur and consequently the principal knickzones. The application of the proposed tool within an experimental catchment located in the Northern Apennines of Italy demonstrated the proper functionality and the potential of its use for different geomorphological and environmental studies. The accurate and cost-effective detection of anomalous changes in stream gradient ensured by SLiX is of great interest and can be useful for studies aimed at unravelling the Earth processes responsible of their formation (e.g., active hillslope processes, such as landslides directly interacting with the streambed, presence of geological structures, and meander cut-off). The applications of SLiX have clear implications for preliminary analyses, at a regional scale in different morpho-climatic contexts, for the hydrological management of river basins and/or to prevent geological hazards related to the fluvial erosional dynamics.

The paper deals with a methodology for quantitative landslide hazard and risk assessments over wide-scale areas. The approach was designed to fulfil the following requirements: (1) rapid investigation of large study areas; (2) use of elementary information, in order to satisfy the first requirement and to ensure validation, repetition and real time updating of the assessments every time new data are available; (3) computation of the landslide frequency of occurrence, in order to compare objectively different hazard conditions and to minimize references to qualitative hazard attributes such as activity states. The idea of multi-temporal analysis set forth by Cardinali et al. (Nat Hazards Earth Syst Sci 2:57–72, 2002), has been stressed here to compute average recurrence time for individual landslides and to forecast their behaviour within reference time periods. The method is based on the observation of the landslide activity through aerial-photo surveys carried out in several time steps. The output is given by a landslide hazard map showing the mean return period of landslides reactivation. Assessing the hazard in a quantitative way allows for estimating quantitatively the risk as well; thus, the probability of the exposed elements (such as people and real estates) to suffer damages due to the occurrence of landslides can be calculated. The methodology here presented is illustrated with reference to a sample area in Central Italy (Umbria region), for which both the landslide hazard and risk for the human life are analysed and computed. Results show the powerful quantitative approach for assessing the exposure of human activities to the landslide threat for a best choice of the countermeasures needed to mitigate the risk