F
Filippo Catani
Researcher at University of Florence
Publications - 184
Citations - 7283
Filippo Catani is an academic researcher from University of Florence. The author has contributed to research in topics: Landslide & Computer science. The author has an hindex of 39, co-authored 142 publications receiving 5371 citations. Previous affiliations of Filippo Catani include University of Padua & Massachusetts Institute of Technology.
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Journal ArticleDOI
Recommendations for the quantitative analysis of landslide risk
Jordi Corominas,C.J. van Westen,Paolo Frattini,Leonardo Cascini,Jean-Philippe Malet,Stavroula Fotopoulou,Filippo Catani,M. van den Eeckhaut,Olga Mavrouli,Federico Agliardi,Kyriazis Pitilakis,Mike G. Winter,Manuel Pastor,Settimio Ferlisi,Veronica Tofani,Javier Hervás,J.T. Smith +16 more
TL;DR: In this article, the authors present recommended methodologies for the quantitative analysis of landslide hazard, vulnerability and risk at different spatial scales (site-specific, local, regional and national), as well as for the verification and validation of the results.
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Artificial Neural Networks applied to landslide susceptibility assessment
TL;DR: In this article, two different ANNs, used in classification problems, were set up and applied: one belonging to the category of Multi-Layered Perceptron (MLP) and the other to the Probabilistic Neural Network (PNN) family.
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Landslide susceptibility estimation by random forests technique: sensitivity and scaling issues
TL;DR: The dimension of parameter space, the mapping unit and the training process strongly influence the classification accuracy and the prediction process, which implies that a careful sensitivity analysis making use of traditional and new tools should always be performed before producing final susceptibility maps at all levels and scales.
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Monitoring, prediction, and early warning using ground-based radar interferometry
TL;DR: In this paper, the authors presented two different applications of the remote sensing technique: the ground-based synthetic aperture radar interferometry, here proposed as a monitoring and early warning support for slope instability.
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Persistent Scatterer Interferometry (PSI) Technique for Landslide Characterization and Monitoring
TL;DR: In this paper, the authors used persistent scatterer interferometry (PSI) and conventional ground-based monitoring techniques to characterize and monitor the Santo Stefano d'Aveto landslide located in the Northern Apennines, Italy.