In this paper a back-analysis of the 2012 Preonzo landslide (Switzerland) collapse is presented. Failure Forecasting Methods (FFMs) have been applied to the pre-collapse time series of displacement obtained by TInSAR (Terrestrial Synthetic Aperture Radar Interferometry). Then, the time series of displacement have been resampled in order to simulate the satellite InSAR (Synthetic Aperture Radar Interferometry) acquisition. The aim is to investigate the potential and the limitations of satellite InSAR monitoring technique for forecasting purposes. Specifically, the low temporal frequency of data acquisition and the ambiguity phase constraints have been accounted for. The achieved results suggest that satellite InSAR technique could be an effective tool for forecasting purposes, even if some issues have still to be faced
Lesson learned from the pre-collapse time series of displacement of the Preonzo landslide (Switzerland) / Moretto, Serena; Bozzano, Francesca; Esposito, Carlo; Mazzanti, Paolo. - In: RENDICONTI ONLINE DELLA SOCIETÀ GEOLOGICA ITALIANA. - ISSN 2035-8008. - ELETTRONICO. - 41:(2016), pp. 247-250. [10.3301/ROL.2016.140]
Lesson learned from the pre-collapse time series of displacement of the Preonzo landslide (Switzerland)
MORETTO, SERENA;BOZZANO, Francesca;ESPOSITO, CARLO;MAZZANTI, PAOLO
2016
Abstract
In this paper a back-analysis of the 2012 Preonzo landslide (Switzerland) collapse is presented. Failure Forecasting Methods (FFMs) have been applied to the pre-collapse time series of displacement obtained by TInSAR (Terrestrial Synthetic Aperture Radar Interferometry). Then, the time series of displacement have been resampled in order to simulate the satellite InSAR (Synthetic Aperture Radar Interferometry) acquisition. The aim is to investigate the potential and the limitations of satellite InSAR monitoring technique for forecasting purposes. Specifically, the low temporal frequency of data acquisition and the ambiguity phase constraints have been accounted for. The achieved results suggest that satellite InSAR technique could be an effective tool for forecasting purposes, even if some issues have still to be facedFile | Dimensione | Formato | |
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