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. 2019 Oct 1;9(1):14137.
doi: 10.1038/s41598-019-50792-y.

Perspectives on the prediction of catastrophic slope failures from satellite InSAR

Tommaso Carlà  1 , Emanuele Intrieri  2 , Federico Raspini  2 , Federica Bardi  3 , Paolo Farina  3 , Alessandro Ferretti  4 , Davide Colombo  4 , Fabrizio Novali  4 , Nicola Casagli  2
Affiliations

Perspectives on the prediction of catastrophic slope failures from satellite InSAR

Tommaso Carlà et al. Sci Rep. .

Erratum in

Abstract

We demonstrate the potential of satellite Interferometric Synthetic Aperture Radar (InSAR) to identify precursors to catastrophic slope failures. To date, early-warning has mostly relied on the availability of detailed, high-frequency data from sensors installed in situ. The same purpose could not be chased through spaceborne monitoring applications, as these could not yield information acquired in sufficiently systematic fashion. 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.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Satellite InSAR data showing precursory deformation leading up to the failure of the investigated open-pit mine slope on 17 November 2016. The purple-colored polygon in the inset delimits the area affected by accelerating trends of displacement. The underlying photos in the main figure and in the inset depict pre- and post-failure instants, respectively. The maps with satellite imagery were created with the ArcGIS PRO 2.4 software (https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview).
Figure 2
Figure 2
Satellite InSAR data showing precursory deformation leading up to the Xinmo landslide on 24 June 2017. The purple-colored polygon in the inset delimits the area affected by accelerating trends of displacement. The underlying photos in the main figure and in the inset depict pre- and post-failure instants, respectively. The maps with satellite imagery were created with the ArcGIS PRO 2.4 software (https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview).
Figure 3
Figure 3
Satellite InSAR data showing precursory deformation leading up to the failure of the Cadia gold mine northern TSF on 9 March 2018. The purple-colored polygon in the inset delimits the area affected by accelerating trends of displacement. The underlying photos in the main figure and in the inset depict pre- and post-failure instants, respectively. The maps with satellite imagery were created with the ArcGIS PRO 2.4 software (https://www.esri.com/en-us/arcgis/products/arcgis-pro/overview).
Figure 4
Figure 4
Example of accelerating trend and resulting inverse velocity regression related to (a,b) the failure of the investigated open-pit mine slope; (c,d) the Xinmo landslide; (e,f) the failure of the Cadia gold mine northern TSF. The red dotted lines indicate the actual failure-time.
Figure 5
Figure 5
Relative frequency distribution of the errors and of the R2 coefficient from the inverse velocity predictions.
See this image and copyright information in PMC

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