A new appraisal of the Ancona landslide based on geotechnical investigations and stability modelling

Abstract

On the night of 13 December 1982, Ancona experienced the catastrophic reactivation of an old and large landslide located along the coast to the west of the city. The outcomes of past and new geotechnical investigations and the data from the 30 year readings of the monitoring instruments have been integrated to redefine and update the actual location of the sliding surfaces. According to the new analysis, the landslide involves four main sliding surfaces with different extents and depths. The deepest surfaces converge at depth in a shear band and their toes are positioned near or beyond the coast. Numerical and analytical modelling of the landslide has been carried out using the newly derived sliding surface geometries. The numerical modelling has allowed a qualitative assessment of the deformation pattern, confirming the geometry of the sliding surfaces derived from the geotechnical investigations. The stability analyses have been performed applying the limit equilibrium method to quantify the instability conditions of the landside. The analyses have been carried out for five stratigraphic-geotechnical scenarios. All of these scenarios show a stability condition near the limit equilibrium.

Brief communication: Using averaged soil moisture estimates to improve the performances of a regional-scale landslide early warning system

“…This region is characterized by a morphology ranging from high mountains in the S-SW to wide plains towards NE. The mountain chain of the region belongs to the northern Apennines, which is a complex fold-and-thrust arcuate orogenic belt that originated in response to the closure of the Ligurian Ocean and the subsequent collision of the European and continental margins which started in the Oligocene (Agostini et al, 2013). The mountainous part of the region is affected by surficial and deep-seated landslides, which can be triggered by short and intense rainfalls or by prolonged rainy periods, respectively (Martelloni et al, 2012).…”

The new landslide inventory of Tuscany (Italy) updated with PS-InSAR: geomorphological features and landslide distribution

“…There is a large number of studies which proposed, applied and compared automated (both pixel and object-based) techniques for landslide mapping with optical data (Hervás et al 2003;Cheng et al 2004;Nichol and Wong 2005;Martha et al 2010;Lu et al 2011).inventory maps. In particular, A-DInSAR techniques such as PSInSAR (Ferretti et al 2000;Colesanti et al 2003), SqeeSAR (Ferretti et al 2011), Stanford Method for Persistent Scatterers (StaMPS) (Hooper et al 2007), Interferometric Point Target Analysis (IPTA) (Werner et al 2003;Strozzi et al 2006), Coherence Pixel Technique (CPT) (Mora et al 2003), Small Baseline Subset (SBAS) (Berardino et al 2003;Casu et al 2006) and Stable Point Network (SPN) (Crosetto et al 2008;Herrera et al 2011) have produced some successful case studies dealing with the detection and the mapping of landslide phenomena, as discussed in Strozzi et al (2006), Colesanti and Wasowski (2006), Lu et al (2012), Meisina et al (2013), Agostini et al (2014), Ciampalini et al (2016), Righini et al (2012) and Raspini et al (2017). Recently, images captured by X-band radar satellite sensors such as the Italian COSMO-Sky Med SAR constellation of four satellites, the German TerraSAR-X satellite and the recently lunched ESA Sentilel-1 can provide very high ground resolution, in the range from 1 to 100 m, and a reduced revisiting time, up to 6 days for Sentinel-1.…”

Advanced Technologies for Landslides (WCoE 2014–2017, IPL-196, IPL-198)

“…Concerning WP 1 the DST-UNIFI performed monitoring activities of unstable slopes in order to estimate the deformational evolution of the landslide events (in space and time) and to implement the most suitable operational early warning systems (EWS) based on different critical situations (Carlà et al 2016;Agostini et al 2014;Bardi et al 2014;Intrieri et al 2013). Several sites have been monitored in Italy (Fig.…”