A PSI-based analysis of landslides in the historic town of Volterra (Italy)

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1 Landslides and Engineered Slopes. Experience, Theory and Practice Aversa et al. (Eds) 2016 Associazione Geotecnica Italiana, Rome, Italy, ISBN A PSI-based analysis of landslides in the historic town of Volterra (Italy) S. Bianchini, F. Pratesi, T. Nolesini, M. Del Soldato & N. Casagli Department of Earth Sciences, University of Firenze, Florence, Italy ABSTRACT: Landslides threaten human lives and structures, especially in urbanized areas, where the density of elements at risk that are sensitive to ground movements is high. Persistent Scatterer Interferometry (PSI) techniques are particularly effective to measure Earth surface displacements for monitoring natural processes just on built-up areas, where many radar benchmarks can be retrieved. This paper aims at detecting terrain motions and their effects on built-up zones, through satellite radar data combined with background data such as aerial imagery and in-situ field surveys on the historic town of Volterra (Tuscany region, Italy). In particular, recent COSMO-SkyMed satellite images acquired in and processed with SqueeSAR technique permitted to improve the knowledge on mechanisms and spatial distribution of landslide phenomena, as well as to carry out a deformation assessment as a single building-scale analysis. Maximum settlement values of some sample buildings were derived from radar measurements, and then cross-compared with constructive features and with geo-morphological conditions on the known landslide areas, as well as validated with on-field evidences. This work turns out to be useful as a preliminary step for further risk management strategies. 1 Introduction Landslide detection and mapping are important issues to take into account, especially on populated and urbanized areas, where potential damages and losses caused by ground instability are stronger due to the higher value of the exposed elements at risk. Persistent Scatterer Interferometry (PSI) technique relies on temporally stable and highly reflective ground elements, typically man-made structures (i.e. buildings, roadways, etc.) or natural elements, in correspondence of which yearly terrain motion rates can be measured with high precision (Ferretti et al. 2001). Consequently, nowadays, PSI data are successfully used for investigating active slow-moving landslide phenomena, and they are particularly effective on urbanized areas where many radar benchmarks can be retrieved (Colesanti & Wasowski 2006, Bianchini et al. 2012). This paper aims at detecting terrain motions and their effects on built-up zones, through satellite radar data combined with background data and in situ field surveys. COSMO-SkyMed satellite images were acquired in on the historic town of Volterra (Tuscany region, Italy) and surrounding area, extensively affected by active and diffuse geomorphological processes such as landslides and badlands. An accurate instability analysis is required, given the cultural heritage of this historic site, known as one of the most important Etruscan settlements and then developed as a medieval center (Sabelli et al. 2012). PSI data obtained through SqueeSAR processing technique (Ferretti et al. 2011) and suitably projected (Rosi et al. 2015, Notti et al. 2014), allowed improving the spatial distribution and inventory of landslide phenomena in the study area. Furthermore, attention was paid to the effects of ground motions on buildings, by carrying out a deformation assessment as a single building-scale analysis derived from Sanabria et al. (2014). As a result, this work allows a better knowledge of the ground instability of Volterra study area, and can support further risk management strategies that would involve the analysis of the most critical settlement conditions of buildings in this landslide-affected historic urban area. 2 methodology The methodological procedure of this work consists in handling PSI displacement measurements and background data such as geological and geomorpho-logical data (e.g. topographic and geological maps, recent HR monoscopic orthophotos), existing landslides inventory and building typology (Fig. 1). 411

2 Figure 1. Workflow of the methodological procedure. In order to increase the confidence degree on interferometric data, PS LOS (Line of Sight) measurements acquired in ascending and descending geometries are projected to real velocity vectors, according to Rosi et al. (2014). Recent PSI data are combined with the background data through radar- and photo-interpretation procedures (Farina et al. 2006), so that the pre-existing landslide inventory is improved and updated to a more recent setting. Then, in order to assess the effects of ground movements on buildings, we apply a method that consists in deriving maximum settlement directions and values of the investigated buildings from PSI displacement data, thanks to IDW (Inverse Distance Weighted) interpolation and foundation design computations (Sanabria et al. 2014). The computed settlement parameters are integrated and cross-compared with constructive features and background geological data on the known landslide-affected areas, as well as validated with on-field evidences. 3 volterra case study 3.1 Geological background The Volterra test area of this work extends up about 18 km 2 (Fig. 2). Volterra is an historical town that includes Etruscan, Roman and medieval settlements, still visible on the present urban centre enclosed by great defensive town-wall. Volterra city centre is located on a tableland at meters a.s.l. (above sea level). The geological setting of the area consists of a Pliocene marine sedimentary succession (Fig. 2). The stratigraphic sequence is represented by a thickness of Early Pliocene marine blue clays, overlapped by Middle-Late Pliocene cemented sandy deposits and uppermost calcarenites. These three lithological units are stacked in horizontal or sub- horizontal layers, slightly dipping about 2 10 Figure 2. Volterra study area: geological map and section with 2x vertical exaggeration. Modified from Sabelli et al., towards NE. Quaternary terrigenous debris lie upon the sandy-clay units, filling the valleys. They mainly derive from the weathering of the upper sandy formations and calcarenites, on which the city itself is built. 3.2 PSI data COSMO-SkyMed satellite radar data in X-band were collected over Volterra area. They consisted of 55 SAR images acquired in ascending geometry with an incidence angle of 31 in the time span and 25 SAR images acquired with an incidence angle of 26 in descending geometry in the period All the SAR scenes were processed by means of the SqueeSAR approach, which is an evolution of PSInSAR (Ferretti et al. 2011). The spatial distributions of PSI LOS mean yearly velocities are shown in Figure 3. For distinguishing stable targets (displayed in a green color) from moving ones, stability thresholds in both descending and ascending orbits are fixed at ±1.0 mm/yr, based on standard deviation values and on threshold choices already tested in scientific literature (Bianchini et al. 2012). The city center of Volterra is confirmed as stable, as proved by the absence of ground motion radar evidence, while the highest mean annual LOS velocities (V LOS ) reach up tens of mm/year within the southwestern part of the study area. Due to the combination of the satellite acquisition geometries with the local topography of the study area, the same slope movements are recorded with opposite sign and different module from ascending to descending orbits, making the interpretation of slope dynamics not immediately intelligible (Bianchini et al. 2015). Thus, given the 412

3 Mean EW-Velocities range 5 15 mm/yr in the most moving areas (Fig. 3). Conversely, vertical components turned out to be negligible, since the most part of detected movements are horizontal downslope motions on slightly inclined slopes and surface ground deformations. Moreover, in order to avoid LOS underestimation and to provide a more feasible quantification of terrain motion rates, the real velocity of PS targets (Vreal) was also computed from the VVERT and VEW values, by following the procedure proposed by Rosi et al. (2014). Results show that the highest rates reach up mm/yr in two localized areas in the southwestern sector of Volterra: Le Colombaie-Il Cipresso and Fontecorrenti, respectively at an elevation of about 340 m and 420 m a.s.l. along the SW slope (Fig. 4). These outcomes are in agreement with ground truth data, provided by GEOPROGETTI company, which consist in two broken inclinometers due to significant sliding movements just on these two sites. 3.3 Landslide and badland Inventory map The geological structure and topography of the Volterra tableland influence the typology and the spatial distribution of mass movements in the area. The layer inclination and the contrast between the impermeable clays, the upper erodible sands and the well-cemented calcarenites determine different kind of landslides and soil erosion processes (Sabelli et al. 2012). In particular, on the southwestern slope of the Volterra hill, the blue clays mainly crop out and the morphology is gentle (Pratesi et al. 2015). Thus, the area turns out to be widely affected by badlands, typical landforms of clayey soils and flows. Figure 3. CSK PSI data distribution and velocity (VLOS descending, VLOS ascending and VEW) on the Volterra study area. availability of both geometries, east-west (VEW) and vertical (VVERT) velocity components are derived from the interpolation of ascending and descending LOS displacement rates, through a vectorbased approach (Rosi et al. 2014, Notti et al. 2014, Bianchini & Moretti 2015). Figure 4. Vreal rates and localization of inclinometers by GEOPROGETTI. 413

4 The shallow colluvial deposits, made up of chaotic detritus, reach up a thickness of 20 meters in the SW sector of the study area and contribute to determine ground instability. As a result, diffuse landsliding of this zone actually refers somewhere to shallow ground deformation related to the instability of the colluvial layer or to surface creep downslope, rather than to landslides. From an altitude of 450 m a.s.l., sands crop out overlapped by calcarenites that outcrop on the opposite hillslope: here a more abrupt morphology prevails, characterized by complex movements and falls due to the undermining of the clayey bases of the hills and consequent retrogressive slope failures that generate very steep, sub-vertical cliffs (balze crags) around the Volterra tableland. The mapping of mass movements performed within this work includes the detection of both badland and landslide phenomena (Fig. 5). Badlands were mapped on the basis of a preexisting map made available by Volterra municipality and dated back to 2005, integrated with recent field observations in 2015 and photo-interpretation. Almost no PS falls into badland areas. The distinction of badland forms known as calanchi (Moretti & Rodolfi 2000) between type A and type B was also carried out: type A gives rise to sharp, deeply incised landforms with unvegetated and knife-edged ridges, corresponding to the maximum badland development stage. Type B is characterized by shallow slides and flows that coexist with concentrated water erosion, thus leading to smoother and more vegetated slopes, corresponding to incipient or residual morphodynamic stages (Rodolfi & Frascati 1979). Landslide mapping was mainly obtained by the individuation of geomorphologic evidences related to landslide phenomena, through the use of recent aerial imagery and through land deformation LOS and real measurements over the space grid of PS points. The pre-existing information on landslides in the study area relies on two landslide inventories provided by Tuscany region and GEOPROGETTI company. While the first one is a database recorded at regional scale, the second one refers to a detailed survey performed in 2010 only on the SW portion of our study area (GEOPROGETTI 2010). These inventories were improved and integrated by means of radar- and photo-interpretation. Starting from the already mapped landslides, the presence and rate of PS data permitted to better verify or enlarge the landslide boundaries and activity, while aerial imagery and field checks allow determining the typology of landslide movements. Surface movements were over-set on badland areas, represented by falls on balze crags or by superficial slides on type B calanchi landscape (Fig. 5). On the two most critical sites, Le Colombaie-Il Cipresso and Fontecorrenti, PS data and insitu surveys permitted to enhance the knowledge, rate of displacement, extension and dynamics of landslide movements. On Le Colombaie-Il Cipresso site many translational and rotational slides were mapped, involving blue clays and colluvial deposits. On Fontecorrenti site, upward the wide badland area, some landslide phenomena were mapped; these ground deformations are partially induced and maintained by gullying and active retrogressive movement of badlands. Some evidences of retreat of the landslide crown scarps were recognized on field and integrated with PS rates, allowing tracing the present boundaries of slide movements(fig. 5). 3.4 Building deformation assessment Figure 5. Badland and Landslide improved Inventory Map of the study area. (1) Fall on balze crags; (2) Badland calanchi type A; (3) Shallow flow on calanchi type B. The black star shows the location of building in Figure 6. A building deformation and damage assessment by means of PSI analysis was performed on the most critical landslide-affected areas on Le Colombaie-Il Cipresso and Fontecorrenti sites that are characterized by the highest ground motion rates. We took into account some representative buildings on these sites and we derived the maximum settlement parameters. Firstly, we performed the Inverse Distance Weighted (IDW) interpolation on PS cumulative displacements to create a continuous displacement-surface from the sample set of PSI point locations. We considered the CSK descending data as the most suitable ones to investigate downward movement on W-facing slopes. 414

5 The resolution of the IDW interpolation has been set as 3 meters, according to the 3 3 m cell size of COSMO-SkyMed satellite images. By virtue of such a resolution, many PS show up on building facades and roofs, fitting well the typical scale of constructive elements. In order to detect movement directions and the related damages on buildings, differential settlements of manufactures are calculated according to the criteria of serviceability limit states, which are those conditions that make the structure unsuitable for its projected use (Eurocode 2010, Ricceri & Soranzo 1985, Skempton et al. 1956). In particular, we used the maximum vertical differential settlement (δ v ) and the angular distortion (β) calculated between the maximum and the minimum cumulative displacement. The maximum vertical differential settlement (δ v ) is defined as the unequal settling of a building, and it is computed as the maximum difference of vertical displacement between two points of the foundation (Eurocode 1994, Bowles 1977, Bjerrum 1963). These two points have been chosen as the centroids of the IDW pixel cells with the maximum and the minimum cumulative displacement derived from PS time series measured during the monitoring period. We calculated the δ v value by using the following equation (1): D δv = D cos θ min_ LOS max_ LOS δ LOS = cosθ (1) where D min_los are respectively the minimum and maximum cumulative displacements measured on the building along the satellite LOS during the monitoring period; δ LOS is the maximum differential settlement between these two measurement points along the LOS; θ is the satellite incidence angle (Fig. 6). Figure 6. Building deformation assessment on an example building in the study area (the building location is pointed out as a black star in Figure 5). It is worth highlighting that the δ LOS value is divided by the cosine of the satellite incidence angle in order to obtain the maximum vertical differential settlement (δ v ) of a given structure (Sanabria et al. 2014) (Fig. 6). The angular distortion (β) is related to the measured vertical settlement, and thus it is computed as the ratio between δ v and the distance (L) between the D min_los measurement points: δ β = v L (2) D min_los were found within the building area, which is the buffer area drawn around the plain-edge of the building and dimensioned accordingly to the cell size resolution (3 m). The use of a buffer as a tolerance area allows taking into account even PS that do not lie within the building plain-edge, but that are the result of a backscattered signal mainly influenced by the structure itself, and also permits avoiding possible shifts in the georeferencing procedure of PSI data stacks, buildings and other cartographical layers. The centroids of the two pixel cells, included within the building area and selected for the calculation of D min_los, define the direction along which differential settlement is dominant (Bianchini et al., 2015). Since differential settlements and related building damages depend on the movements of the foundation soil, as well as on the type of the structure itself, the amount and direction of the computed parameters δ v and β were cross-compared with background data, among which are the geological setting, the improved badland and landslide inventory maps, the building typology information. Finally, validation and interpretation of the estimated PSI settlements were obtained by matching up δ v and β to the geological setting and constructive features, as well as to local failures and building crack patterns recognized by in-situ observations Building example Different buildings homogenously distributed in the southwestern sector of the study area and located at different topographic elevations along the slope (from 340 m a.s.l. up to 470 m a.s.l.) were taken into account. They are characterized by different construction typologies, age and foundations, as well as by different foundation ground. We show here the results on an alabaster warehouse that consists of a reinforced concrete structure located at an altitude of 410 m a.s.l. The area is characterized by a 12 m-thick colluvial layer that lies on the clayey unit, and it is 415

6 affected by a wide dormant translational landslide. The landslide slip surface is 18-m depth between upper geothecnically poor clays characterized by low shear strength and lower clays with better geotechnical properties, i.e., a higher shear strength (GEOPROGETTI 2010). The structure has direct foundations consisting of a grade beam placed directly on the ground. The IDW interpolation of PS data exhibits high cumulative displacements up to about 40 mm, with spatially increasing values from SE to NW. Accordingly, the maximum differential settlement δ v shows a considerable value with a SE-NW vector orientation (29.86 mm). The PS data spatial pattern, as well as δ v and β directions were compared and validated with insitu observations. Intense damages were surveyed on the building, resulting in millimetric-centimetric cracks on external walls. The location and pattern of damages, normal to tension stresses, resulted in agreement with the orientation of the δ v vector (Fig. 6). 4 DISCUSSION and conclusions The PSI analysis in the Volterra study area permitted to enhance the knowledge on spatial distribution, displacement rates and types of mass movements. The calanchi badlands are located on the southern side of Volterra tableland, where clayey deposits extensively crop out. Badland areas were mapped relying on aerial imagery, pre-existing inventory and field checks. We detected 18 badlands, among which 13 are mostly active and bare (type A) and 5 are vegetated, intended as incipient or residual phenomena (type B). While the historic town centre turns out to be stable, landslide phenomena occur all over the study area, but their different typologies are influenced by the outcropping lithologies. Detection and mapping of landslides were based on PSI data integrated with pre-existing inventories, photointerpretation of recent orthophotos and in-situ observations. The improved landslide inventory map consists of 116 phenomena. On the northern hillside, characterized by limestones and sandy formation, complex landslides prevail. On the balze crags in the NW sector of the area with a well-developed stratigraphic sequence of clays overlapped by sands and calcarenites, some falls are recognized due to the undermining of clays and retreat of the calcarenitic crags. On type B calanchi, many surface flows or slides take place, mapped over or next to badland areas. The most critical zone of the Volterra study area is the southwestern sector where many translational/rotational landslides are mapped. PSI CSK data show ground motion rates up to mm/year over the monitoring period on the Le Colombaie-Il Cipresso and Fontecorrenti sites. On both sites, landsliding is increased by thick colluvial deposits that contribute to the ground instability of the area. Moreover, on Fontecorrenti site the terrain deformation measured by PSI data could be also connected to the area of influence of the retrogressive movement of the downhill badland area. In order to evaluate impacts of mass movements on the urban fabric, we performed a deformation assessment on some buildings of the study area, throughout the PSI-based computation of differential settlement parameters. Values and directions of these settlement features were cross-compared with background data and crack patterns detected during a recent in-situ survey, in order to validate the estimated building deformations. The building damage assessment was performed by considering descending CSK PSI data acquired in the recent three-year time interval and analyzing their deformation time series. As no restoration activities were undertaken over the selected structures during the acquisition period, the in-situ surveys on buildings performed during 2014 can be considered reliable. It is worth to underline that on one hand PS velocities detected on rocks and natural elements can be reasonably ascribed to a landslide movement, on the other hand, the PS displacements measured on buildings can be the result of an interaction between soil instability and the mechanisms of the soil-structure system, and damages potentially derive from this interaction. In conclusion, this work scans active ground displacements on the area around the historic town Volterra and turns out to be useful as a preliminary step for further risk management strategies that would involve the analysis of the most critical badland- and landslide-affected areas and potential consequences on buildings. aknowledgements The authors would like to thank GEOPROGETTI company (geologists Francesca Franchi and Emilio Pistilli) for making the geological and geotechnical data on Volterra available. All of the COSMO-SkyMed SAR images were processed by Tele-Rilevamento Europa by means of the SqueeSAR TM technique. The landslide inventory map was provided by the Tuscany Region ( Research and Innovation in the environmental field, 2009) within the DIANA (Dati Interferometrici per l ANalisi Ambientale) Italian project. 416

7 Further data and information on the investigated area of the Volterra site are available on the City Council website: references Bianchini, S., Cigna, F., Righini, G., Proietti, C., Casagli, N Landslide HotSpot Mapping by means of Persistent Scatterer Interferometry. Environmental Earth Sciences, 67(4), Bianchini, S., Moretti, S Analysis of recent ground subsidence in the Sibari plain (Italy) by means of satellite SAR interferometry-based methods. International Journal of Remote Sensing, 36(18), Bianchini, S., Pratesi, F., Nolesini, T., Casagli, N Building deformation assessment by means of Persistent Scatterer Interferometry analysis on a landslideaffected Area: The Volterra (Italy) case study. Remote Sens, 7, ; doi: /rs Bjerrum, L Allowable settlement of structures. In Proceedings of the 3rd European Conference on Soil Mechanics and Foundation Engineering, Wiesbaden, Germany, October Bowles, J.E Foundation Analysis and Design; Mc Graw Hill Publications: New York, NY, USA. Colesanti, C. & Wasowski, J Investigating landslides with space-borne Synthetic Aperture Radar (SAR) interferometry. Eng. Geol., 88, Eurocode, EC, 7: Geotechnical Design. Available online: en pdf (accessed on 10 October 2014). Eurocode, Basis of Structural Design. Available online: (accessed on 12 October 2014). Farina, P., Colombo, D., Fumagalli, A., Marks, F., Moretti, S Permanent Scatterers for landslide investigations: outcomes from the ESA-SLAM project. Engineering Geology, 88, Ferretti, A., Fumagalli, A., Novali, F., Prati, C., Rocca, F., Rucci, A A new algorithm for processing interferometric datastacks: SqueeSAR. IEEE Trans. Geosci. Remote Sens., 49, Ferretti, A., Prati, C., Rocca, F Permanent scatterers in SAR interferometry. IEEE Trans. Geosci. Remote Sens., 39, GEOPROGETTI studio associato company, Indagini geognostiche e sismiche per l analisi dell assetto geologico e geomorfologico del versante Sud di Volterra. Report for the Volterra Municipality, Moretti, S. & Rodolfi, G A typical calanchi landscape of the Eastern Appennine margin (Atri, Central Italy): geomorphological features and evolution. Catena, 40, Notti, D., Herrera, G., Bianchini, S., Meisina, C., García- Davalillo, J.C., Zucca, F A methodology for improving landslide PSI data analysis. Int. J. Remote Sens., 35. doi: / Pratesi, F., Nolesini, T., Bianchini, S., Leva, D., Lombardi, L., Fanti, R., Casagli, N Early Warning GBInSAR-based Method for Monitoring Volterra (Tuscany, Italy) City Walls. J. Sel. Top. Appl. Earth Obs. Remote Sens., doi: /jstars Ricceri, G. & Soranzo, M An analysis on allowable settlement of structures. Riv. Ital. Geotec., 4, Rodolfi, G & Frascati, F Cartografia di base per la programmazione degli interventi in aree marginali Area rappresentativa dell Alta Val D Era. Memorie illustrative della carta geomorfologica. Annali Istituto Sperimentale per lo Studio e la Difesa del Suolo 10: Rosi A., Agostini, A., Tofani V., Casagli N A procedure to map subsidence at the regional scale using the Persistent Scatterer Interferometry (PSI) technique. Remote Sens., 6, ; doi: / rs Sabelli, R., Cecchi, G., Esposito, A.M Mura etrusche di Volterra. Conservazione e Valorizzazione; Bientina, Ita.: La Grafica Pisana, Italy. Sanabria, M.P., Guardiola-Albert, C., Tomás, R., Herrera, G., Prieto, A., Sánchez, H., Tessitore, S Subsidence activity maps derived from DInSAR data: Orihuela case study. Nat. Hazards Earth Syst. Sci., 14, Skempton, A.W. & McDonalds, D.H Allowable settlements of buildings. Proc. ICE. 5,