This paper presents recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results. The methodologies described focus on the evaluation of the probabilities of occurrence of different landslide types with certain characteristics. Methods used to determine the spatial distribution of landslide intensity, the characterisation of the elements at risk, the assessment of the potential degree of damage and the quantification of the vulnerability of the elements at risk, and those used to perform the quantitative risk analysis are also described. The paper is intended for use by scientists and practising engineers, geologists and other landslide experts.

Testing innovative procedures and techniques to update landslide inventory maps is a timely topic widely discussed in the scientific literature. In this regard remote sensing techniques – such as the Synthetic Aperture Radar Differential Interferometry (DInSAR) – can provide a valuable contribution to studies concerning slow-moving landslides in different geological contexts all over the world. In this paper, DInSAR data are firstly analysed via an innovative approach aimed at enhancing both the exploitation and the interpretation of remote sensing information; then, they are complemented with the results of an accurate analysis of survey-recorded damage to facilities due to slow-moving landslides. In particular, after being separately analysed to provide independent landslide movement indicators, the two datasets are combined in a DInSAR-Damage matrix which can be used to update the state of activity of slow-moving landslides. Moreover, together with the information provided by geomorphological maps, the two datasets are proven to be useful in detecting unmapped phenomena. The potentialities of the adopted procedure are tested in an area of southern Italy where slow-moving landslides are widespread and accurately mapped by using geomorphological criteria.

This paper shows the results of a study aimed at quantitatively estimating—in terms of direct (repair) costs, at large scale (1:5000)—the slow-moving landslide risk to a road network assumed as undamaged as well as the consequences to the same network in damaged conditions. The newly conceived methodological approaches address some challenging tasks concerning (i) the hazard analysis, which is expressed in terms of probability of occurrence of slow-moving landslides with a given intensity level that, in turn, is established based on empirical fragility curves, and (ii) the consequence analysis, which brings to the generation of time-dependent vulnerability curves. Their applicability is successfully tested in a case study in the Campania region (southern Italy) for which both very high-resolution DInSAR data and information gathered from in situ surveys on the severity of damage sustained by the selected road sections are available. Benefits associated with the use of the obtained results in informed decision-making processes are finally discussed.