Perspectives on the prediction of catastrophic slope failures from satellite InSAR
- 1University of Firenze, Earth Sciences Department, Firenze, Italy (federico.raspini@unifi.it)
- 2Geoapp s.r.l., Via Francesco Veracini 30/G, 50144, Florence, Italy
- 3TRE ALTAMIRA, Ripa di Porta Ticinese 79, 20143, Milan, Italy
In many landslide studies, the possibility to predict future behaviour is still a major concern. To date, early-warning systems have mostly relied on the availability of detailed, high-frequency data from sensors installed in situ. Methods deducing reliable failure predictions have been largely applied at local scale, where in situ monitoring systems can be installed.
The same purpose could not be chased through spaceborne monitoring applications, as these could not yield information acquired in sufficiently systematic fashion: the low data sampling frequency of most of the satellite systems hampered the possibility to retrieve the necessary details of tertiary creep characterized by accelerating deformation. So far, the lack of systematic information on ground displacement acquired at regional scale was another serious limit hampering the application of failure prediction methods at wide scale. Such limitations can be partially solved through the exploitation of new generation spaceborne platforms.
The launch of Sentinel-1 mission opened a new opportunity for InSAR monitoring applications thanks to the increased acquisition frequency, the regularity of acquisitions and the policy on data access. We demonstrate the potential of satellite Interferometric Synthetic Aperture Radar (InSAR) to identify precursors to catastrophic slope failures.
Here we present three sets of Sentinel-1 constellation images processed by means of multi-interferometric analysis. We detect clear trends of accelerating displacement prior to the catastrophic failure of three large slopes of very different nature: an open-pit mine slope, a natural rock slope in alpine terrain, and a tailings dam embankment. We determine that these events could have been located several days or weeks in advance. The results highlight that satellite InSAR may now be used to support decision making and enhance predictive ability for this type of hazard.
How to cite: Raspini, F., Carlà, T., Intrieri, E., Bardi, F., Farina, P., Ferretti, A., Colombo, D., Novali, F., and Casagli, N.: Perspectives on the prediction of catastrophic slope failures from satellite InSAR, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-13158, https://doi.org/10.5194/egusphere-egu2020-13158, 2020