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Alessandro Simoni
Researcher at University of Bologna
Publications - 51
Citations - 2374
Alessandro Simoni is an academic researcher from University of Bologna. The author has contributed to research in topics: Landslide & Debris flow. The author has an hindex of 20, co-authored 46 publications receiving 1899 citations. Previous affiliations of Alessandro Simoni include University of Washington.
Papers
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The Direct Shear Strength and Dilatancy of Sand-gravel Mixtures
Alessandro Simoni,Guy T. Houlsby +1 more
TL;DR: In this article, a total of 87 direct shear tests in a large direct-shear-box apparatus have been used to investigate the strength and dilatancy of sand-gravel mixtures.
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Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach
Matteo Berti,Mario L. V. Martina,Silvia Franceschini,Sara Pignone,Alessandro Simoni,Marco Pizziolo +5 more
TL;DR: In this article, a new method for evaluating rainfall thresholds based on Bayesian probability is proposed, which is simple, statistically rigorous, and returns a value of landslide probability (from 0 to 1) for each combination of the selected rainfall variables.
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Field observations of a debris flow event in the Dolomites
TL;DR: A debris flow event occurred in June 1997 in the Dolomites (Eastern Alps, Italy) and was directly observed in the field and recorded by a video camera near its initiation area as discussed by the authors.
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Landslide prediction, monitoring and early warning: a concise review of state-of-the-art
TL;DR: In this article, the authors reviewed the recent advances and the state-of-the-art in the essential components of the landslide hazard assessment, such as landslide susceptibility analysis, runout modeling, landslide monitoring and early warning, were reviewed.
Probabilistic rainfall thresholds for landslide occurrence using a Bayesian approach
Matteo Berti,Mario L. V. Martina,Silvia Franceschini,Sara Pignone,Alessandro Simoni,Marco Pizziolo +5 more
TL;DR: In this article, a new method for evaluating rainfall thresholds based on Bayesian probability is proposed, which is simple, statistically rigorous, and returns a value of landslide probability (from 0 to 1) for each combination of the selected rainfall variables.