Posters

NH3.6

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.

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

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

X3.185 |
EGU2019-2248
Kuang-Jung Tsai, Yie-Ruey Chen, Ming-Hsi Lee, and Tsai-Tsung Tsai
Hall X3
Hall X3
Hall X3
X3.188 |
EGU2019-2612
Yie-Ruey Chen, Chwen-Ming Chang, Yao-Lin Wang, Kuang-Jung Tsai, Shun-Chieh Hsieh, and Yi-Ching Lu
Hall X3
X3.189 |
EGU2019-2983
Raquel Melo, José Luís Zêzere, Jorge Rocha, and Sérgio Cruz Oliveira
Hall X3
Hall X3
Hall X3
Hall X3
Hall X3
X3.194 |
EGU2019-5745
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
Hall X3
X3.195 |
EGU2019-5841
Wei Shen, Matteo Berti, and Tonglu Li
Hall X3
Hall X3
Hall X3
X3.198 |
EGU2019-8941
Guoli Zhang, Ming Wang, and Kai Liu
Hall X3
X3.199 |
EGU2019-11183
Mauro Lanfranchi, Andrew Cameron, and Paul Hallett
Hall X3
X3.200 |
EGU2019-17730
Enrico D'Addario, Leonardo Disperati, Nazario Broda, Elisa Mammoliti, and Michele Pio Papasidero
Hall X3
X3.201 |
EGU2019-18107
Calibrating and processing SAR images from Sentinel-1 for the purpose of soil moisture extraction
(withdrawn)
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
Hall X3
X3.202 |
EGU2019-17952
Helen K. French, Dominika Krzeminska, Hans Martin Hanslin, Trygve Aamlid, and Anne-Grete Buseth Blankenberg
Hall X3
Hall X3
X3.204 |
EGU2019-6754
Rainfall-induced landslides forecasting physically based on a coupled hydrological-geotechnical framework
(withdrawn)
Hongjun Bao
Hall X3
X3.205 |
EGU2019-11070
Valentina Colaiuda, Barbara Tomassetti, Annalina Lombardi, and Marco Verdecchia