Slow-moving landslides are a natural hazard which affects wide areas in the world causing relevant economic damage to structures and infrastructures. To this reason, the analysis of landslide-induced consequences plays a key role in risk prevention and mitigation activities. The thesis shows a general methodology which can be used to forecast spatial and temporal evolution of building vulnerability in urban settlements affected by slow-moving and intermittent landslides. Multi-level and integrated analysis of landslide kinematics and exposed elements allows to assess at different scales of representation and at different levels of accuracy, future conditions of damage of existing facilities.
Satellite Radar Interferometry and in particular the Differential SAR Interferometry (DInSAR) technique has been successfully applied as a remote-sensing tool to provide information both on spatial and temporal landslide evolution and on interaction with structures in urban areas. Integration of C and X-band SAR data (acquired between 2002 and 2016) with conventional monitoring techniques allows to reach a thorough knowledge of landslide kinematics; subsequently, structural analyses to detect the relationship between slope movements and building damage have been performed, by using qualitative, semi-quantitative and quantitative approaches.
Such methodology has been tested in Moio della Civitella urban settlement, Salerno Province, whose territory is affected by several slow-moving landslides. At small scale of representation, preliminary cause-effect relationship and the updating of landslide inventory map have been provided; at medium scale of analysis, vulnerability zoning map through matrix-approach and influence of vulnerability factors on performance of structures through fragility curves approach, have been defined. Finally, at a detailed scale, structural behavior of buildings has been investigated by means of analytical or numerical analyses.
The proposed methodology could be applied to other scenarios affected by similar phenomena and once validated, can be valuably used for damage analysis and forecasting
