Pierluigi Confuorto

Multivariate Statistical approach vs. Deterministic physically based model for landslide susceptibility assessment

We present a comparison between the results of two landslide susceptibility analyses approaches: multivariate (Logistic Regression) and deterministic–physically based (SHALSTAB). In order to assess the Landslide Susceptibiliy Index, five different predisposing factors to landslide occurrence (slope, aspect, land cover, distance to streams and rocky scarps) for the first one and material density, material friction angle, material hydraulic transmissivity, bulk cohesion and depth to potential shear plane for the second have been set up respectively.Two different sectors of the urban area of the Phlegraean Fields, within the municipalities of Naples and Pozzuoli, have been selected for the application of the two methodologies: the Agnano Plain hillslopes (slope maximum elevation: 190 m a.s.l.) and the Astroni volcano (max. elev.: 253 m a.s.l.). The results have been compared and tested (ROC/AUC curves) allowing further considerations about the benefits and the constraints of each model.

25 years of satellite InSAR monitoring of ground instability and coastal geohazards in the archaeological site of Capo Colonna, Italy

For centuries the promontory of Capo Colonna in Calabria region, southern Italy, experienced land subsidence and coastline retreat to an extent that the archaeological ruins of the ancient Greek sanctuary are currently under threat of cliff failure, toppling and irreversible loss. Gas extraction in nearby wells is a further anthropogenic element to account for at the regional scale. Exploiting an unprecedented satellite Synthetic Aperture Radar (SAR) time series including ERS-1/2, ENVISAT, TerraSAR-X, COSMO-SkyMed and Sentinel-1A data stacks acquired between 1992 and 2016, this paper presents the first and most complete Interferometric SAR (InSAR) baseline assessment of land subsidence and coastal processes affecting Capo Colonna. We analyse the regional displacement trends, the correlation between vertical displacements with gas extraction volumes, the impact on stability of the archaeological heritage, and the coastal geohazard susceptibility. In the last 25 years, the land has subsided uninterruptedly, with highest annual line-of-sight deformation rates ranging between -15 and -20 mm/year in 2011-2014. The installation of 40 pairs of corner reflectors along the northern coastline and within the archaeological park resulted in an improved imaging capability and higher density of measurement points. This proved to be beneficial for the ground stability assessment of recent archaeological excavations, in an area where field surveying in November 2015 highlighted new events of cliff failure. The conceptual model developed suggests that combining InSAR results, geomorphological assessments and inventorying of wave-storms will contribute to unveil the complexity of coastal geohazards in Capo Colonna.

Implementation of DInSAR methods for the monitoring of the archaeological site of Hera Lacinia in Crotone (Southern Italy)

The monitoring of cultural heritage and archeological sites affected by ground deformation is significant for their preservation and protection. The Differential Synthetic Aperture Radar interferometry is here applied to investigate the displacements occurring in the Capo Colonna area (Crotone municipality, Southern Italy), a site whose name derives from the only remaining column of the old Hera Lacinia temple, belonging to the Magna Graecia city of Kroton and dating to the 6th century BC. Processing and interpretation of SAR data has been carried out thanks to the availability of TerraSAR-X images, acquired in the time-span 2008-2010. The results obtained show the protraction of a well-known subsiding trend, connected to a mix of natural (lithostratigraphic setting, seismic activity, eustatic sea-level changes) and anthropogenic causes, the latter represented by the local on-shore and off-shore gas extraction activity. Displacement velocities up to 15 mm/yr have been identified along the satellite Line of Sight (LOS), both in the ascending and in the descending orbits. These two displacement rates have been combined to obtain the vertical component, which has been calculated in 30 mm over two years of monitoring. Moreover, the installation of 80 corner reflectors in October 2014 provided an improvement to the SAR interpretation, allowing not only to further investigate about the relationship between gas extraction and vertical motion but also to focus on the coastal erosion affecting the archeological site.

Remote Sensing for Natural or Man-Made Disasters and Environmental Changes

Natural and man-made disasters have become an issue of growing concern throughout the world. The frequency and magnitude of disasters threatening large populations living in diverse environments, is rapidly increasing in recent years across the world due to demographic growth, inducing to urban sprawls into hazardous areas. These disasters also have far-reaching implications on sustainable development through social, economic and environmental impact. This chapter summarises three scientific contributions from relevant experiences of the British Geological Survey and the Federico II University of Naples, where remote sensing sensors have been playing a crucial role to potentially support disaster management studies in areas affected by natural hazards. The three cases are: the landslide inventory map of St. Lucia island, tsunami-induced damage along the Sendai coast (Japan) and the landslide geotechnical characterization in Papanice (Italy). For each case study we report the main issue, datasets available and results achieved. Finally, we analyse how recent developments and improved satellite and sensor technologies can support in overcoming the current limitations of using remotely sensed data in disaster management so to fully utilize the capabilities of remote sensing in disaster management and strength cooperation and collaboration between relevant stakeholders including end users.

Application of a Statistical Approach to Landslide Susceptibility Map Generation in Urban Settings

Landslide susceptibility maps are effective tools for the mitigation of risks caused by such geological events. In line with recent scientific trends and thanks to the availability of detailed geological data, landslide susceptibility modeling, by means of statistical methodologies, has gained increasing consideration. The present work is based on a methodology widely employed in the field of ecology to draw prediction maps for the occurrence probability of certain species (MaxEnt). The study area is located in Palma Campania, a town sited in the peri-vesuvian area (in the province of Napoli, southern Italy) and characterized by a significant presence of pyroclastic soils, affected by several landslide events, one of which killed eight people in 1986. In this work, eleven geomorphological and geological predisposing factors were selected, based on previous experiences of landslides in peri-vesuvian areas and following several field surveys. Results were critically evaluated using a validation dataset (Receiver Operating Characteristic—ROC curves), by means of Sensitivity-Specificity graphs estimating Area Under Curve (AUC), and other tests such as the Jackknife and response curves, which highlighted the major role played by a number of factors. The consistent agreement between our results and the existing official map demonstrates the validity of the adopted procedure for emergency and land planning.

Multi-temporal assessment of building damage on a landslide-affected area by interferometric data

Slow-moving landslides are widespread in different geological settings all over the world and they often are cause of significant damage to existing man-made structures. For such reason, a considerable interest towards innovative approaches useful to provide information on their evolution and on the interaction with existing buildings has grown among the scientific community and land management institutions. To this purpose, the combined use of C-band satellites and X-band Synthetic Aperture Radar sensors, has been successfully applied in several analyses aimed at the detection of spatial and temporal effects, in term of buildings damage induced by landslides. This work provides a general approach useful to investigate, at different levels of detail, the cause-effect relationship. The proposed methodology has been applied to the urban settlement of Moio della Civitella (Salerno province, Italy), whose whole territory is affected by several slow-moving landslides. C and X-band SAR data (acquired between 2002 and 2014), integrated with field survey of structural damage, enhanced an accurate examination of landslide effects on the urban texture of Moio della Civitella. The results allowed to generate empirical fragility curves for buildings on the study area. These curves can be used as a tool to forecast the future likelihood of the damage occurrence. Finally, the behavior of a masonry building aggregate has been assessed analyzing Differential Synthetic Aperture Radar Interferometry (DInSAR) time-series pre- and post-repair intervention, thus providing information also about the efficacy of restoration works.

Slow-moving landslide monitoring with multi-temporal TerraSAR-X data by means of DInSAR techniques in Crotone Province (Southern Italy)

Surface movements and landslides monitoring with satellite-based DInSAR techniques is becoming more and more widespread among research groups and scientific community. The SAR Differential Interferometry (DInSAR) is one of the most powerful devices for monitoring deformation processes on the Earth surface. Here, a dataset of TerraSAR-X StripMap imagery covering almost the whole Crotone province territory, located in the south of the Italian peninsula, has been selected. The time span goes from April 2008 to June 2010 and from August 2013 to October 2014. Crotone province is severely affected by landslide phenomena, due to the geological and geomorphological context, as well as to the physical and mechanical properties of the involved materials. According to an accurate bibliographic and newspaper research, in agreement with field surveys, as to find the most suitable cases for the use of the satellite interferometry, different case studies have been selected. Hence, the attention has been concentrated on several urban settlements. The most important are Papanice, Cutro, Santa Severina, San Mauro Marchesato, Ciro, Crucoli, in which, several landslide evidences, affecting roads and buildings, have been recognized. Particular attention has been focused on slow and intermittent landslides, highly detectable by DInSAR techniques. In this work, two different multitemporal interferometry (MTI – Wasowsky et al., 2014) approaches and two different software packages have been used and compared in order to identify benefits/constraint of each MTI approach and each software. Such approaches are: a) the “permanent” (or “persistent”, or “point-like”) scatterers (PS - Ferretti et al., 2001) and the “small baseline subset approach” (SBAS - Berardino et al., 2002; Lanari et al., 2004) implemented both in the SARscape software, developed by the SARMAP team, and on SUBSOFT processor, this last based on the Coherent Pixel Technique (CPT - Mora et al., 2003, Blanco et al., 2008), developed by the Remote Sensing Laboratory (RSLab) group, from the Universitat Politecnica de Catalunya (UPC). For every technique, displacement time series have been obtained and compared. The interferometric analysis has shown good results, being able to identify displacement rates up to 4 cm/year, and also allowing to redraw landslide boundaries, previously identified in the Hydrogeological Setting Plan of the Calabria region (2001), updating their state of activity, as well. Moreover, being the available dataset antecedent to the landslides’ reactivations, the adopted DInSAR techniques have been able to recognize precursor stages of slope failures, hence confirming the reliability of SAR methods as powerful monitoring and prediction tools.