Giulia Tessari

Building Damage Risk by Modeling Interferometric Time Series

Predicting building damage due to subsidence phenomena is a great challenge in the field of risk management, and moreover in the process of disaster risk reduction. The proposed damage assessment integrates measurements obtained from satellite synthetic aperture radar (SAR) observations with a semiempirical model, which schematizes buildings as equivalent laminated beams. The importance of each of the parameters involved in the semiempirical method has been evaluated to understand the applicability of the model in different urban contexts. SAR monitoring and structural modeling have been connected to investigate a densely urban area, the southern part of the city of Rome. Information obtained from the two fields allowed for the generation of risk maps.

Variation in the Occurrence of Rainfall Events Triggering Landslides

We analyze the climatic features of the Vicenza Province (NE Italy) and the characteristics of the exceptional rainfall event that hit the area in November 2010, triggering a huge number of landslides. Our analysis aims at identifying the hydrological variable related to the triggering of the recorded instabilities and the recent variation in the occurrence of rainfall events inducing landslides.

Phase and amplitude analyses of SAR data for landslide detection and monitoring in non-urban areas located in the North-Eastern Italian pre-Alps

Abstract The main aim of this paper is to exploit information obtained from satellite SAR data to detect and monitor instability phenomena affecting hilly and scarcely urbanized areas, overtaking some of the restrictions due to the presence of thick vegetation. To this end, phase and amplitude analyses of COSMO-SkyMed SAR data were carried out on two landslides located in the North-Eastern Italian pre-Alps: Cischele roto-translational slide and Val Maso rotational slide—earth flow. In the first case, the careful choice of processing parameters allowed to evaluate landslide displacement fields considering the phase difference between SAR acquisitions. In the second case, the speed of movement and the deep changes in morphology and vegetation induced by the landslide did not allow to apply DInSAR techniques; in this case the variation in the amplitude between SAR acquisitions allowed to detect the area affected by the instability. Obtained results show that methods and techniques to analyse satellite SAR data could be further refined in order to provide useful tools for landslide mapping and monitoring.

Testing Sentinel-1A Data in Landslide Monitoring: A Case Study from North-Eastern Italian Pre-Alps

Open image in new window The main aim of this study is to test the effectiveness of Sentinel-1A Synthetic Aperture Radar (SAR) data in monitoring scarcely urbanized slopes affected by slow-moving instabilities. To this end, geological and geomorphological surveys were carried out, satellite SAR data were processed and a GPS network system was installed. The study area, named Rovegliana, is located in the North-Eastern sector of the Italian pre-Alps. Rovegliana slopes are covered by eluvial, colluvial and landslide debris deposits which are mainly affected by superficial phenomena such as creep and soil slips. In situ surveys and Advanced Differential SAR Interferometry (A-DInSAR) processing of ERS, ENVISAT and COSMO Sky-MED SAR data pointed out that the instabilities are active with constant velocities up to 10 mm/year. Only the central and eastern sectors of the area were subjected to an acceleration after an exceptional rainfall event occurred in November 2010. GPS monitoring started in October 2015 and has been implemented through four campaigns made up of high precision geodetic measures of possible soil deformations of 22 vertices of a Global Navigation Satellite System (GNSS) static network. These vertices have been connected by a network to obtain a robust system. Comparing results from historical interferometric data, GPS measurements and interferometry processing of Sentinel SAR data acquired in the period 2015–2016, make it possible to verify if Sentinel data, characterized by short revisiting time, can be used as useful tool to define the spatio-temporal evolution of the recorded instabilities, overcoming the limits of applying interferometric techniques caused by temporal decorrelation due to the presence of vegetation cover, increasing the possibility to obtain significant information about landslide dynamics from SAR data. Moreover, we expect that the high number of planned acquisitions will improve the accuracy of deformation measurements.

Risk of building damage by modeling interferometric time series

Predicting building damages due to ground movements caused by subsidence phenomena is a great challenge in the field of Risk Management, moreover in the process of Disaster Risk Reduction. This damage assessment integrates measurements obtained from satellite SAR observations with an intermediate semi-empirical model, which schematizes buildings as equivalent laminated beams. The monitoring and modelling stages have been embedded to investigate densely urban areas. Two test sites have been examined: the Southern part of the city of Rome (Italy) and a recently constructed building in Astana (Kazakhstan). Furthermore, the importance of each of the parameters involved in the semi-empirical method for modelling building deformation has been evaluated to understand the applicability of the modelling in different urban contexts, with different knowledge of the urban pattern.