The paper deals with an ongoing research aimed at investigating the relationships between the kinematic features of slow-moving landslides affecting urban areas and the related effects on exposed buildings. These relationships are expressed in terms of changes of damage severity levels over time also considering the factors governing – in different way – the onset and the development of the damage. The building response to slow-moving landslide was analysed by exploring longterm and multi-temporal monitoring/surveying information gathered from conventional and innovative techniques along with background geological, geomorphological and geotechnical data. To this aim, the analysis starts from a well-documented case study in Calabria Region (southern Italy) and then it extends to four other areas in Italian Apennines with similar geological settings, landslide types and built-up features. The results achieved can help setting up more reliable models for consequence forecasting to be used in quantitative risk analyses.
Investigating the factors governing the damage occurrence on buildings exposed to slow-moving landslide risk
Gianfranco Nicodemo
;Dario Peduto;Davide Luongo;Settimio Ferlisi;
2024-01-01
Abstract
The paper deals with an ongoing research aimed at investigating the relationships between the kinematic features of slow-moving landslides affecting urban areas and the related effects on exposed buildings. These relationships are expressed in terms of changes of damage severity levels over time also considering the factors governing – in different way – the onset and the development of the damage. The building response to slow-moving landslide was analysed by exploring longterm and multi-temporal monitoring/surveying information gathered from conventional and innovative techniques along with background geological, geomorphological and geotechnical data. To this aim, the analysis starts from a well-documented case study in Calabria Region (southern Italy) and then it extends to four other areas in Italian Apennines with similar geological settings, landslide types and built-up features. The results achieved can help setting up more reliable models for consequence forecasting to be used in quantitative risk analyses.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.