This paper aimed to develop and test a data-driven model for the identification of road sectors that are susceptible to be hit by shallow landslides triggered in slopes upstream of infrastructure. Most susceptible road traits were those located below steep slopes with a limited height (lower than 50 m), where sediment connectivity is high. The results of the susceptibility analysis can give asset managers indispensable information on the relative criticality of the different roads.

Multi-sensor advanced DInSAR analyses have been performed, in order to evaluate the land subsidence evolution in a 20-year period, in the Alto Guadalentín Basin where the highest rate of man-induced subsidence (>10 cm/yr-) of Europe had been detected. The control mechanisms have been examined comparing the advanced DInSAR data with conditioning and triggering factors (i.e. isobaths of Plio-Quaternary deposits, soft soil thickness and piezometric level).

A methodology based on Persistent Scatterer Interferometry (PSI) is proposed in order to disentangle the contribution of different processes that act at different spatio-temporal scales in land subsidence (i.e. vadose zone processes as swelling/shrinkage of clay soils, soil consolidation and fluid extraction). The methodology was applied in different Italian geological contexts characterized by natural and anthropic processes (i.e. a Prealpine valley and the Po Plain in northern Italy).

This manuscript defines a reliable methodology for shallow landslides triggering zones assessment at site-specific or local scales by using a well-established physically based model (TRIGRS-unsaturated) based on the calibration of the model at slope scale using soil hydrological behavior analyzed through a continuous field monitoring. Moreover, the paper analyzes the effects on triggering zones assessment of taking into account for different unit mapping of the slope soils of a studied area.