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On October 25, 2011, an extreme rainfall event affected a wide area along the coasts of Cinque Terre (eastern Liguria, northern Italy). Particularly, in the Vernazza catchment, the event triggered hundreds of shallow landslides and a debris flood that caused three casualties. Investigation of the slope stability after the event was carried out aiming at defining the most effective mitigation measures which may be adopted in future land use planning. To this objective, a susceptibility model was produced and a series of scenarios were simulated using probabilistic methods. The susceptibility model has provided information about landslide conditioning factors on which to act for reducing\ud landslide occurrence and therefore the associated risk. The simulations have taken into consideration the following alternative types of mitigation measures: (1) restoration of abandoned terraces, (2) reforestation of abandoned terraces, (3) use of local structural measures over stretches of potentially unstable hillsides and (4) avoidance of any intervention. The advantages and the disadvantages of the proposed mitigation measures for shallow landslide risk are discussed considering the results of the simulations and taking into account their complex interaction with environmental, historical, cultural and socio-economic aspects. The results show that the most effective mitigation strategy for reducing landslide risk at short term consists of applying structural measures over potentially unstable slopes. However, a longterm programme promoting the development of agricultural or forestry practices on terraced slopes is necessary. In fact, the\ud simulations indicate that if no measures are applied to avoid the degradation of the terraced areas, landslide areal frequency would\ud inevitably increase

Agricultural terraces represent one of the best ways to prevent land degradation in hilly and mountainous landscapes. However, it is widely recognized that terraced slopes are threatened by agricultural land abandonment. In the literature, very few studies have quantitatively examined the influence of agricultural abandonment on the stability of terraced slopes. The goal of this research is to investigate the relationships between landslide magnitude and land use conditions of agricultural terraced slopes. In particular, Light Detection And Ranging (LiDAR) elevation data, coupled with aerial photo interpretation, were used for the computation of shallow landslide mobilized volumes on terraced slopes affected by an intense rainfall event. We performed the analysis within the Vernazza basin, a small Mediterranean coastal catchment located in the “Cinque Terre” area (Liguria, northwestern Italy), comparing pre‐event and post‐event LiDAR datasets. The results revealed that abandoned terraced slopes have been affected by a higher amount of mobilized debris volumes than still‐cultivated terraces. Furthermore, terraces abandoned for a short time (less than 25–30 years) resulted in the most hazardous land use class, showing erosion rates that were approximately 2 and 3 times higher than terraced slopes abandoned a long time ago (more than 25–30 years) and still‐cultivated terraces, respectively. These findings highlight that land abandonment and agricultural mismanagement can intensify the magnitude of rainfall‐induced shallow landslides. Copyright © 2016 John Wiley & Sons, Ltd.

The spatial distribution of shallow landslides is strongly influenced by different climatic conditions and environmental settings. This makes difficult the implementation of an exhaustive monitoring technique for\ud correctly assessing the landslide susceptibility in different environmental contexts. In this work, a unique methodological strategy, based on the statistical implementation of the generalized additive model (GAM), was performed. This method was used to investigate the shallow landslide predisposition of four sites with different geological, geomorphological and land-use characteristics: the Rio Frate and the Versa catchments (Southern\ud Lombardy) and the Vernazza and the Pogliaschina catchments (Eastern Liguria). A good predictive overall accuracy was evaluated computing by the area under the ROC curve (AUROC), with values ranging from 0.76 to 0.82 and estimating the mean accuracy of the model (0.70–0.75). The method showed a high flexibility, which led to a good identification of the most significant predisposing factors for shallow landslide occurrence\ud in the different investigated areas. In particular, detailed susceptibility maps were obtained, allowing to identify the shallow landslide prone areas. This methodology combined with the use of the rainfall thresholds \ud for triggering shallow landslides may provide an innovative tool useful for the improvement of spatial planning and early warning systems

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