New space-borne radar sensors enable multi-scale monitoring of potentially unstable slopes thanks to wide-area coverage (tens of thousands km2), regular long-term image acquisition schedule with increasing re-visit frequency (weekly to daily), and high measurement precision (mm). In particular, the recent radar satellite missions e.g., COSMO-SkyMed (CSK), Sentinel-1 (S-1) and improved multi-temporal interferometry (MTI) processing techniques allow timely delivery of information on slow ground surface displacements. Here we use two case study examples to show that it is possible to capture pre-failure slope strains through long-term MTI-based monitoring. The first case is a retrospective investigation of a huge ~500ML m3 landslide, which occurred in Sept. 2016 in a large, active open-cast coal mine in central Europe. We processed over 100 S-1 images acquired since Fall 2014. The MTI results showed that the slope that failed had been unstable at least since 2014. Importantly, we detected consistent displacement trends and trend changes, which can be used for slope failure forecasting. Specifically, we documented significant acceleration in slope surface displacement in the two months preceding the catastrophic failure. The second case of retrospectively captured pre-failure slope strains regards our earlier study of a small ~50 m long landslide, which occurred on Jan. 2014 and caused the derailment of a train on the railway line connecting NW Italy to France. We processed 56 CSK images acquired from Fall 2008 to Spring 2014. The MTI results revealed pre-failure displacements of the engineering structures on the slope subsequently affected by the 2014 slide. The analysis of the MTI time series further showed that the displacements had been occurring since 2009. This information could have been used to forewarn the railway authority about the slope instability hazard. The above examples indicate that more frequent and consistent image acquisitions by the new radar satellites represent the key improvement for MTI-based slope monitoring. The forecasting of potential slope failures from space is now more feasible.
Forecasting slope failures from space-based synthetic aperture radar (SAR) measurements / Wasowski, Janusz; Bovenga, Fabio; Nutricato, Raffaele; Nitti, Davide Oscar; Chiaradia, Maria Teresa; Tijani, Khalid; Morea, Alberto. - ELETTRONICO. - (2017). (Intervento presentato al convegno AGU fall meeting tenutosi a New Orleans, LA nel December 11-15 , 2017).
Forecasting slope failures from space-based synthetic aperture radar (SAR) measurements
Fabio Bovenga;Raffaele Nutricato;Davide Oscar Nitti;Maria teresa Chiaradia;Khalid Tijani;Alberto Morea
2017-01-01
Abstract
New space-borne radar sensors enable multi-scale monitoring of potentially unstable slopes thanks to wide-area coverage (tens of thousands km2), regular long-term image acquisition schedule with increasing re-visit frequency (weekly to daily), and high measurement precision (mm). In particular, the recent radar satellite missions e.g., COSMO-SkyMed (CSK), Sentinel-1 (S-1) and improved multi-temporal interferometry (MTI) processing techniques allow timely delivery of information on slow ground surface displacements. Here we use two case study examples to show that it is possible to capture pre-failure slope strains through long-term MTI-based monitoring. The first case is a retrospective investigation of a huge ~500ML m3 landslide, which occurred in Sept. 2016 in a large, active open-cast coal mine in central Europe. We processed over 100 S-1 images acquired since Fall 2014. The MTI results showed that the slope that failed had been unstable at least since 2014. Importantly, we detected consistent displacement trends and trend changes, which can be used for slope failure forecasting. Specifically, we documented significant acceleration in slope surface displacement in the two months preceding the catastrophic failure. The second case of retrospectively captured pre-failure slope strains regards our earlier study of a small ~50 m long landslide, which occurred on Jan. 2014 and caused the derailment of a train on the railway line connecting NW Italy to France. We processed 56 CSK images acquired from Fall 2008 to Spring 2014. The MTI results revealed pre-failure displacements of the engineering structures on the slope subsequently affected by the 2014 slide. The analysis of the MTI time series further showed that the displacements had been occurring since 2009. This information could have been used to forewarn the railway authority about the slope instability hazard. The above examples indicate that more frequent and consistent image acquisitions by the new radar satellites represent the key improvement for MTI-based slope monitoring. The forecasting of potential slope failures from space is now more feasible.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.