This extended abstract presents the results of a study aimed at predicting the direct and indirect slow-moving landslide-induced damage to an undamaged road network by way of performance indicators and Monte-Carlo simulations. The probabilistic analyses are conceived to enhance the combined use of available remote-sensing (DInSAR) data and empirical fragility curves generated for Quantitative Risk Analysis (QRA) purposes.
Probabilistic analysis of the performance of a road network affected by slow-moving landslides
S. Ferlisi
;A. Marchese;D. Peduto;
2023-01-01
Abstract
This extended abstract presents the results of a study aimed at predicting the direct and indirect slow-moving landslide-induced damage to an undamaged road network by way of performance indicators and Monte-Carlo simulations. The probabilistic analyses are conceived to enhance the combined use of available remote-sensing (DInSAR) data and empirical fragility curves generated for Quantitative Risk Analysis (QRA) purposes.File in questo prodotto:
Non ci sono file associati a questo prodotto.
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
