CHARACTERIZATION AND MODELLING OF GEOLOGICAL INSTABILITIES THROUGH REMOTE SENSING TECHNIQUES AND NUMERICAL SIMULATIONS



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CHARACTERIZATION AND MODELLING OF GEOLOGICAL INSTABILITIES THROUGH REMOTE SENSING TECHNIQUES AND NUMERICAL SIMULATIONS Ph.D. candidate: GIULIA TESSARI, III course Tutor: Dott. MARIO FLORIS Cycle: XXVII Abstract Analyses of ground displacements can help to define the evolution of areas affected by instability phenomena and identify their triggering factors. To this end, Synthetic Aperture Radar (SAR) satellite data can be used to collect direct measurements of superficial deformations in instability-prone areas. Results from remote sensing analyses can be then compared with outcomes from numerical simulations, and in particular with displacement or velocity fields, to validate numerical modelling and eventually recalibrate the simulation of instabilities, predisposing and triggering conditions. The contribution of SAR data in numerical simulation of ground deformations was tested on two landslides occurred in the Piedmont sector of North-Eastern Italian Alps, and in subsidence and sinkhole - prone areas located in the Jordanian coast of the Dead Sea. The aim is to develop tools for investigating instability phenomena and monitoring their spatial and temporal evolution. Full Report Introduction Knowing the dynamic of geological instabilities is necessary to understand and forecast activation or re-activation of deformation phenomena, and possibly avoid catastrophic consequences. Numerical simulations allow reproducing slope behavior under some hypotheses but their accuracy is strongly connected to the amount of available input data. Unfortunately it is not easy to have all the necessary information and most of the required parameters can be set based on reasonable assumptions that consequently can be verified through classical field tools and geological survey or remote sensing techniques. Direct or remote sensing techniques can be used to characterize and monitor ground deformation phenomena, and particularly to identify surface displacements. These information can be used to verify the suitability of numerical model predictions and the adequacy of preliminary hypotheses. An innovative approach could consider a surface displacement map, as the starting point to re-create a model of instability phenomena. This application requires precise velocity data characterized by an adequate resolution, depending on the phenomenon analysed. Recently this method was applied to earthquakes with satisfying results (Wright at al., 2006). This work is aimed to determine which is the contribution of SAR satellite data in investigating instabilities phenomena, in particular landslides and sinkholes. This methodological approach was tested in different conditions to understand its applicability and how to optimize the results overcoming some of the observed limits. Methods Satellite remote sensing techniques have been shown to lead to accurate large-scale surface displacement mapping. Specifically Interferometric Synthetic Aperture Radar (InSAR) technique allows to measure accurate land displacement. Furthermore, not only deformation but even the evolution of displacements can be estimated, combining InSAR information from a large number of SAR images and analyzing changes on the signal phase. This technique is defined D-InSAR (Differential Interferometric SAR) and PS InSAR (Ferretti et al., 2001) and SBAS techniques (Berardino et al., 2002) represent the main methodology proposed. But D-InSAR techniques have some limits of applicability. For example, due to high radar viewing angles, the current space-borne systems can detect only a fraction of the horizontal component of the movement. In fact not every geometrical configurations and slope 1

exposition can be surveyed. Further problems are connected with the presence of dense vegetation. In these situations amplitude can be exploited to identify surface deformations (Casu et al., 2011). Applying the above mentioned techniques it is possible to observe deformation patterns and surface movements. Comparing displacement obtain from monitoring stage with results from numerical modelling, let to understand if numerical prevision is satisfying and the evolution of slope dynamic is correct. Case studies and results Val Maso Landslide, Valli del Pasubio Val Maso landslide, located in Valli del Pasubio municipality (NW sector of Vicenza Province), was triggered by an exceptional flood event occurred in November 2010. I tried to obtain more information about this phenomenon analysing a stacking of RADAR satellite images. Because of the dense vegetation and the aspect of the area, outcomes of PS and SBAS DInSAR technique were not satisfying. That is why InSAR data were analysed concentrating on amplitude changes of the signal instead on studying the phase. A stack of nine COSMO-SkyMed images acquired on 2010 were used. Seven of these images are antecedent the November 2010 flood and the others are subsequent the event. Mean of amplitudes was calculated for the images before and after the flood, and ratio between these mean amplitudes was evaluated. Results showed it is possible to detect the effect of ground deformations from the data analysed and to define the Figure 1 Optical image of Val Maso landslide (Valli del Pasubio, VI) compared with the ratio between mean amplitudes of InSAR images before and after the flood event. Blue areas correspond to ratio values higher than 1.5, where the amplitude of the signal increases after the landslide event; red areas correspond to low values of the amplitude ratio, smaller than 0.5. Cischele Landslide, Recoaro Terme boundary of the landslide. In fig. 1 ratio between mean amplitudes before and after the event is shown. The study area is locate in Recoaro Terme municipality, on the North-West of the Province of Vicenza. After the flood of November 2010, severe damages were noticed on the buildings and on the Provincial street. These phenomena are related to a reactivation of a landslide whose behaviour seems to be connected to climatic conditions. Data obtained from field and laboratory analysis were used on the creation of the model. Ground displacements of the slope were evaluated analysing data obtained from PS available for Cischele area, obtained processing SAR images acquired by ERS and ENVISAT satellites, from May 1995 to May 2000 and from September 2004 to June 2010, respectively. Ground velocity and displacements are measured along the line of sigh of the satellites. Only information obtained from descending orbits are available. This limitation prevents the accurate evaluation of the direction of the movements. Furthermore, InSAR images acquired by COSMO-SkyMed satellites over the flood that hit Vicenza Province in 2010 were analysed. Both PS and SBAS techniques were applied. 2

Interferograms were generated using InSAR images and a 90 meters resolution Digital Elevation Model (DEM), SRTM DEM. The time series interval considered was constrained by the acquisition of the satellites. Only 14 descending images were available from April 2010 to September 2012. Unfortunately variation in surface condition between two different acquisitions produces Figure 2 Velocity obtained from SBAS analysis in Recoaro Terme (VI). loss of coherence. This effect is strongly connected to the presence of vegetation in the area. It was possible to overcome this problem through an accurate calibration of the filtering parameters, extending the coverage of the final displacement map. Results showed the entity of displacements appeared smaller than the movements observed on the damaged buildings: maximum velocity of 12 mm/year was measured against an observed displacement of some centimetres. This can be caused both to the non-exact knowledge of the direction of displacements and to the velocity of the phenomenon that was probably too fast to be measured applying these techniques. Ghor Al Haditha Sinkholes, Dead Sea, Jordan DInSAR techniques were applied to monitor sinkholes affecting the Jordan coast of the Dead Sea. The Dead Sea is a hypersaline terminal lake located in a pull-apart basin, which is one of the major components of the Jordan Dead Sea Transform fault system. This area is prone to earthquakes and soil liquefaction. Most of the area is characterized by highly karstic and fractured rock formations that are connected with faults. Karstic conduits extend from the land into the sea. Over the Dead Sea surface, about 80 x 15 km, the rainfall is 70 mm/yr while the evaporation is 2 m/yr. Since the 1960s, the Dead Sea level is dropping at an increasing rate: from about 60 cm/yr in the 1970s up to 1 m/yr in the 2000s. From about the mid-1980s, sinkholes appeared more and more frequently over and around the emerged mudflats and salt flats. Strong subsidence and landslides also affect some segments of the coast. Nowadays, several thousands of sinkholes attest that the degradation of the Dead Sea coast is worsening. I focused on Ghor Al Haditha area, located in the South-Eastern part of the lake coasts (lat. 31.313456 ; long. 35.530737 ). Figure 3 Velocity obtained from SBAS analysis in Ghor Al Haditha (Jordan). Detail of SAR interferometry fringes connected to a sinkhole displacement from May to June 2012. 3 SAR date acquired by three different sensors, ERS, ENVISAT and COSMO- SkyMed.

70 ERS images from 1992 to 2009 and 30 ENVISAT images from 2003 to 2010 were processed. SBAS technique were applied to define surface velocity and displacement maps. Because of the resolution of these sensors, consisting on 25 m 2, it was possible to clearly define areas affected by subsidence but the single sinkholes could not be detected because of the small size of each punctual event, that is generally varying from few meters to a hundred meters diameter. Furthermore, SBAS was applied to 23 COSMO-SkyMed SAR satellite images from December 2011 to May 2013. The high resolution of these data (3m x 3m) and the shorter revisiting time allowed to have precise information of the displacement of punctual sinkholes beyond the overall subsidence of the coast. A specific sinkhole was considered to understand its temporal evolution (fig. 3). On the basis of the results from D-InSAR processing, a simplified analytical model was implemented. Vertical and horizontal components of the surface displacement field obtained from analysis of SAR images have been used as input data to derive geophysical parameters of the source and in particular to estimate the volumetric strain of the phenomenon. Position, dimension and mechanism were obtained. General conclusions Space-borne SAR data allowed to obtain important information about the dynamics of instability phenomena, which degree of precision depends on several factors, as vegetation density and surface velocity. We tested the applicability of D-InSAR methods in different conditions to obtain useful information to re-create the phenomena through numerical modelling. When rapid displacements overcome the maximum detectable surface velocities between two consecutive SAR acquisitions and changing in land cover produces a complete coherence loss, the amplitude of the signal can be analyse instead of the phase. In the Val Maso landslide, a rapid mapping of surface deformation is possible, providing important hints to manage post-event emergency situations. Despite the dense vegetation in Cischele area, SBAS technique could assess a component of the landslide displacement, through an accurate calibration of some processing parameters. Thanks to the flat geometry of the site and the almost absent vegetation covering, analysis of sinkholes in Jordan Dead Sea coast gave precise information about ground deformation and helpful data to model a sinkhole and to define its geometry and volume reduction. In these favourable conditions, SAR data allow one to predict the occurrence of geological instabilities, characterise their extension, model their evolution and define an early warning system to prevent catastrophic events. References BERARDINO, P., FORNARO, G., LANARI, R., SANSOSTI, E. 2002. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE Transactions on Geoscience and Remote Sensing, 40(11), 2375-2383. CASCINI, L., FORNARO, G., PEDUTO, D. 2009. Analysis at medium scale of low-resolution DInSAR data in slow-moving landslide-affected areas. ISPRS Journal of Photogrammetry and Remote Sensing, 64, 598-611. FERRETTI, A., PRATI, C., ROCCA, F. 1999. Monitoring terrain deformation using multi-temporal SAR images. In Proc. CEOS SAR Workshop, ESA-CNE, Toulouse, France. FERRETTI, A., PRATI, C., ROCCA, F. 2001. Permanent scatterers in SAR interferometry. IEEE Transactions on Geoscience and Remote Sensing, 38 (5), 2202-2212. CASU, F., MANCONI, A., PEPE, A., LANARI, R. 2011. Deformation Time-Series generation in areas characterized by large displacement dynamics: the SAR amplitude Pixel-Offset SBAS technique. IEEE Transactions on Geoscience and Remote Sensing, 49 (7). KARAKI, N. A., CLOSSON, D., KASSA, S.,2012. Field trip to the Dead Sea. EAFE Workshop in Dead Sea Sinkholes: Causes, Effects & Solutions,23-25 September 2012, Amman, Jordan. WRIGHT T.J., EBINGER C., BIGGS J., AYELE A., YIRGU G., KEIR D., STORK A., 2006. Magmamaintained rift segmentation at continental rupture in the 2005 Afar dyking episode. Nature, Vol. 442. 4

SUMMARY OF ACTIVITY IN THIS YEAR Courses: R.J. ANGEL: Scientific Communication Course, Dipartimento di Geoscienze, Università degli Studi di Padova R. GENEVOIS: Metodi di analisi di stabilità dei versanti in terra e roccia, Dipartimento di Geoscienze, Università degli Studi di Padova. Communications: TESSARI G., FLORIS M., 2014. Phase and amplitude analysis of SAR data for landslide characterization and detection in non-urban area. SARscape User Group 2014 (Roma, October 2 nd, 2014) BISSON A., COLA S.,TESSARI G., FLORIS M. Floating anchors in landslide stabilization: the Cortiana case in North-Eastern Italy. IAEG XII Congress (Torino, September 15-19 2014). Posters: TESSARI G., CLOSSON D., KARAKI N. A., ATZORI S., FIASCHI S., FLORIS M., PASQUALI P., RICCARDI P. and Characterization of seepage surface from Space-borne RADAR interferometry stacking techniques, Southern Dead Sea area, Jordan. EGU General Assembly 2014. Vol. 16, EGU2014-3963. Publications: BISSON A., COLA S.,TESSARI G., FLORIS M. Floating anchors in landslide stabilization: the Cortiana case in North-Eastern Italy. Engineering Geology for Society and Territory, Vol. 2, 2014. TESSARI G., FLORIS M. SAR interferometry for Landslides detection and characterization in hilly and vegetated areas. In fase di sottomissione ad una rivista scientifica internazionale Other: Internship: SARMAP S.A., Purasca, Switzerland. Applications of SARScape and DInSAR techniques to analyze ground deformations. June - September 2014. 5