Landslides are ubiquitous geomorphological phenomena with potentially catastrophic consequences. In several countries landslide mortality can be higher than that of any other natural hazard. Predicting landslides is a difficult task that is of both scientific interest and societal relevance that may help save lives and protect individual properties and collective resources. The session focuses on innovative methods and techniques to predict landslide occurrence, including the location, time, size, destructiveness of individual and multiple slope failures. All landslide types are considered, from fast rockfalls to rapid debris flows, from slow slides to very rapid rock avalanches. All geographical scales are considered, from the local to the global scale. Of interest are contributions investigating theoretical aspects of natural hazard prediction, with emphasis on landslide forecasting, including conceptual, mathematical, physical, statistical, numerical and computational problems, and applied contributions demonstrating, with examples, the possibility or the lack of a possibility to predict individual or multiple landslides, or specific landslide characteristics. Of particular interest are contributions aimed at: the evaluation of the quality of landslide forecasts; the comparison of the performance of different forecasting models; the use of landslide forecasts in operational systems; and investigations of the potential for the exploitation of new or emerging technologies e.g., monitoring, computational, Earth observation technologies, in order to improve our ability to predict landslides. We anticipate that the most relevant contributions will be collected in the special issue of an international journal.

Co-organized as GM7.10
Convener: Filippo Catani | Co-conveners: Xuanmei Fan, Fausto Guzzetti, Binod Tiwari
| Thu, 11 Apr, 10:45–12:30, 14:00–18:00
Room L6
| Attendance Thu, 11 Apr, 08:30–10:15
Hall X3

Attendance time: Thursday, 11 April 2019, 08:30–10:15 | Hall X3

X3.185 |
Kuang-Jung Tsai, Yie-Ruey Chen, Ming-Hsi Lee, and Tsai-Tsung Tsai
X3.188 |
Yie-Ruey Chen, Chwen-Ming Chang, Yao-Lin Wang, Kuang-Jung Tsai, Shun-Chieh Hsieh, and Yi-Ching Lu
X3.189 |
Raquel Melo, José Luís Zêzere, Jorge Rocha, and Sérgio Cruz Oliveira
X3.194 |
Veronica Zumpano, Francesca Ardizzone, Alessia Basso, Francesco Bucci, Mauro Cardinali, Federica Fiorucci, Piernicola Lollino, Mario Parise, Luca Pisano, Paola Reichenbach, Francesca Santaloia, Michele Santangelo, Paola Salvati, and Janusz Wasowski
X3.195 |
Wei Shen, Matteo Berti, and Tonglu Li
X3.198 |
Guoli Zhang, Ming Wang, and Kai Liu
X3.199 |
Mauro Lanfranchi, Andrew Cameron, and Paul Hallett
X3.200 |
Enrico D'Addario, Leonardo Disperati, Nazario Broda, Elisa Mammoliti, and Michele Pio Papasidero
X3.201 |
Calibrating and processing SAR images from Sentinel-1 for the purpose of soil moisture extraction
Maria Teresa Melis, Vasil Yordanov, Francesco Onorato Perseu, Marco Scaioni, Elisa Vuillermoz, Stefania Da Pelo, Daniela Pani, Stefano Loddo, Simonetta Paloscia, Emanuele Santi, Simone Pettinato, and Giacomo Fontanelli
X3.202 |
Helen K. French, Dominika Krzeminska, Hans Martin Hanslin, Trygve Aamlid, and Anne-Grete Buseth Blankenberg
X3.204 |
Rainfall-induced landslides forecasting physically based on a coupled hydrological-geotechnical framework
Hongjun Bao
X3.205 |
Valentina Colaiuda, Barbara Tomassetti, Annalina Lombardi, and Marco Verdecchia