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
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:
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