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Landslide hazards have significant social, economic, and environmental impact. This work provides a critical review of the main existing literature using satellite data for mapping landslides. We created and examined an extensive bibliographic database from Web of Science (WoS) consisting in 291 outputs from > 1,000 authors who studied almost 700,000 landslides across all continents, for a total of 52 countries represented with China and Italy on top of the list with more authors. The outputs are equivalent to ~ 5% of the whole landslide-related production for the period 1996–2022, with a 600% increase in the number of papers after 2014 driven by the availability of Sentinel-1 and Sentinel-2 data. Analysis of the geographical location across the 66 different countries analysed shows that, within the total number of contributions, the satellite imagery was used to detect and map two main types of landslides: flows and slides. When specified in the manuscripts, the events have been triggered by rainfall (104 cases), earthquakes (32 cases), or both (17 cases). Slope instabilities in these areas were predominantly identified through manual detection (40%); but since 2020, the advent of artificial intelligence is suppressing all other techniques. Despite the undisputed progress of EO-based landslide mapping over the last 26 years, which makes it a consolidated tool for many landslide-related applications, challenges still remain for an effective and operational use of EO images for landslide detection and mapping, and we provide a perspective for future applications considering the existing and the planned SAR satellite missions. [ABSTRACT FROM AUTHOR]

Identifying the instability areas provides useful information about the recognition of the vulnerable zones and, thus, helps to potentially decrease the harm to the infrastructure and the hazard conditions in inhabited areas. In this regard, morphometric parameters and tectonic setting are widely employed in mapping, modelling and understanding of instability processes. The present study is aimed to analyse the combined effects of slope morphometry (slope gradient, slope curvature, local relief), of lithology, of drainage density and of tectonic setting on the distribution of landslides. The study area is located in the Mesima Basin that lies in the central part of the Calabria region (southern Italy). The morphometric analysis was carried out by geographic information system (GIS) techniques, whereas the geomorphic attributes were computed by a digital elevation model (DEM). The recognized landslides and faults were digitized and stored in a GIS geo-database that allowed the construction of relative density maps. A total of 1 991 landslides and 231 tectonic lineaments were recognized and mapped. The distribution of the collected data suggests that the occurrence of landslides is not random. Indeed, the research highlights as the lithology, the fault density, the slope gradient and the local relief play an important role in determining the landslide occurrence. The used approach is aimed to reinforce the knowledge about the validity of the application of morphometric analysis to the landslide susceptibility. The Mesima Basin is a poorly studied area of the Calabria from a geomorphological viewpoint. Indeed, previous researches focused mainly on geological and on tectonic aspects, as well as on instability phenomena in the Mesima surroundings. Thus, this paper takes a step forward with respect to previous studies because it augments the knowledge about the relationship between faults, morphometric features and the occurrence of landslide. [ABSTRACT FROM AUTHOR]

Perceptions of risk are a key issue when seeking to develop systems, practices and policies to protect local populations. This is particularly evident when risk mitigation strategies involve non-structural measures such as relocation and warning systems which presuppose the active involvement of the communities in question. This study adopts an interdisciplinary approach to studying the perceptions, knowledge and opinions on landslide risk amongst residents in Sarno, a small town in Southern Italy which was hit by disastrous landslides on 5-6 May 1998. The paper presents the results of a survey conducted in the months of March, April and May 2013 using a purpose-designed questionnaire. The survey was conducted using face-to-face interviews with 100 residents, 60 of whom live inside the so-called 'red zone', a territory declared at high residual risk soon after the events of 1998. The questionnaire included questions relating to perceived risk exposure, trust in institutions responsible for risk management, evaluations of risk mitigation measures and the early-warning strategy. The results of the study clearly emerges, amongst other issues, that the organisms which are responsible for risk management in Sarno need to develop more effective communication strategies in order to transmit knowledge about the actions implemented to reduce landslide risk in the area. [ABSTRACT FROM AUTHOR]

A case study of a debris slide (estimated volume of about 35,000 m) is described in this paper. This slide occurred in April 2009 in the North Western Italian Alps (Aosta valley) and damaged the SR25 road along the Valgrisenche valley. Ground investigations started with severe safety and logistic issues being posed. Given the need to open as soon as possible the road, the design of the landslide stabilization works was carried out using a 'design as you go' approach. The stabilization measures were conceived to be flexible in order to allow for changes and integration during construction, in line with the progressive refinement of the geological-geotechnical slope model being developed. Back analysis by means of the limit equilibrium method (LEM) and the finite element method (FEM) was used. Groundwater level rise following heavy rainfall and spring snow melting was found to be the main cause of the debris slide. The stabilization works were designed by using both the LEM and FEM methods. The stability conditions of the engineered slope were assessed based on the available performance monitoring data. [ABSTRACT FROM AUTHOR]