Articles | Volume 13, issue 1
https://doi.org/10.5194/nhess-13-85-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-13-85-2013
© Author(s) 2013. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Brief communication "Landslide Early Warning System: toolbox and general concepts"
E. Intrieri
Department of Earth Sciences, University of Studies of Florence, via La Pira 4, 50121, Florence, Italy
G. Gigli
Department of Earth Sciences, University of Studies of Florence, via La Pira 4, 50121, Florence, Italy
N. Casagli
Department of Earth Sciences, University of Studies of Florence, via La Pira 4, 50121, Florence, Italy
F. Nadim
NGI/ICG (Norwegian Geotechnical Institute/International Centre for Geohazards), P.O. Box 3930 Ullevål Stadion, 0806, Oslo, Norway
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Landslides are a threat not only to people but also to important infrastructure, like highways. Nowadays there are several monitoring systems that are able to detect slope displacements in order to give prompt alarms. On the other hand, such instruments produce a huge amount of information, which is often not totally used and which can also represent an issue for data storage and transmission. In this paper we explain how we dealt with the large quantity of data provided by one of these tools.
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This paper represents one of the main outcomes of a 3-year PhD program at the Earth Sciences Department of the University of Firenze (Centre of Competence of the Italian Civil Protection for geohazards). The main objectives of this paper were to investigate the landslide kinematics through the monitoring activity using GB-InSAR technology and to validate the stabilization works effectiveness using the coupled action of the GB-InSAR and the observational method (OM).
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Forecasting a landslide collapse is a key element in risk reduction, but it is also a very difficult task due to scientific difficulties in predicting a complex natural event and the severe social repercussions caused by a false or missed alarm.
In order to help decision makers, we propose a method of increasing the confidence when making landslide predictions. This study also helps understand how geology affects landslide predictability by introducing a predictability index.
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Landslides are a threat not only to people but also to important infrastructure, like highways. Nowadays there are several monitoring systems that are able to detect slope displacements in order to give prompt alarms. On the other hand, such instruments produce a huge amount of information, which is often not totally used and which can also represent an issue for data storage and transmission. In this paper we explain how we dealt with the large quantity of data provided by one of these tools.
Federica Ferrigno, Giovanni Gigli, Riccardo Fanti, Emanuele Intrieri, and Nicola Casagli
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Short summary
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This paper represents one of the main outcomes of a 3-year PhD program at the Earth Sciences Department of the University of Firenze (Centre of Competence of the Italian Civil Protection for geohazards). The main objectives of this paper were to investigate the landslide kinematics through the monitoring activity using GB-InSAR technology and to validate the stabilization works effectiveness using the coupled action of the GB-InSAR and the observational method (OM).
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Nat. Hazards Earth Syst. Sci., 16, 2501–2510, https://doi.org/10.5194/nhess-16-2501-2016, https://doi.org/10.5194/nhess-16-2501-2016, 2016
Short summary
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Forecasting a landslide collapse is a key element in risk reduction, but it is also a very difficult task due to scientific difficulties in predicting a complex natural event and the severe social repercussions caused by a false or missed alarm.
In order to help decision makers, we propose a method of increasing the confidence when making landslide predictions. This study also helps understand how geology affects landslide predictability by introducing a predictability index.
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