We present the continuous monitoring of ground deformation at regional scale using ESA (European Space Agency) Sentinel-1constellation of satellites. We discuss this operational monitoring service through the case study of the Tuscany Region (Central Italy), selected due to its peculiar geological setting prone to ground instability phenomena. We set up a systematic processing chain of Sentinel-1 acquisitions to create continuously updated ground deformation data to mark the transition from static satellite analysis, based on the analysis of archive images, to dynamic monitoring of ground displacement. Displacement time series, systematically updated with the most recent available Sentinel-1 acquisition, are analysed to identify anomalous points (i.e., points where a change in the dynamic of motion is occurring). The presence of a cluster of persistent anomalies affecting elements at risk determines a significant level of risk, with the necessity of further analysis. Here, we show that the Sentinel-1 constellation can be used for continuous and systematic tracking of ground deformation phenomena at the regional scale. Our results demonstrate how satellite data, acquired with short revisiting times and promptly processed, can contribute to the detection of changes in ground deformation patterns and can act as a key information layer for risk mitigation.

We provide a step-by-step analysis and discussion of the 'PSI-based matrix approach', a methodology employing ground deformation velocities derived through Persistent Scatterer Interferometry (PSI) for the assessment of the state of activity and intensity of extremely to very slow landslides. Two matrices based on PSI data are designed respectively for landslides already mapped in preexisting inventories and for newly identified phenomena. Conversely, a unique intensity scale is proposed indiscriminately for both. Major influencing factors of the approach are brought to light by the application in the 14km 2 area of Verbicaro, in Northern Calabria (Italy). These include lack of PSI data within the landslide boundaries, temporal coverage of the available estimates, and need of field checks as well as the operative procedures to set the activity and intensity thresholds. For the area of Verbicaro, we exploit 1992-2011 PSI data from ERS1/2 and RADARSAT1/2 satellites, projecting them along the maximum slope directions. An activity threshold of ±5mm/year is determined by applying the average projection factor of local slopes to the PSI data precision. The intensity threshold between extremely and very slow phenomena (16mm/year) is reduced bỹ 20% to account for temporal and spatial averages being applied to attribute representative velocities to each landslide. The methodology allows assessing the state of activity and the intensity for 13 of the 24 landslides premapped in the 2007 inventory and for two newly identified phenomena. Current limitations due to characteristics and spatial coverage of PSI data are critically tackled within the discussion, jointly with respective implications.

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This work is focused on deformation activity mapping and monitoring using Sentinel-1 (S-1) data and the DInSAR (Differential Interferometric Synthetic Aperture Radar) technique. The main goal is to present a procedure to periodically update and assess the geohazard activity (volcanic activity, landslides and ground-subsidence) of a given area by exploiting the wide area coverage and the high coherence and temporal sampling (revisit time up to six days) provided by the S-1 satellites. The main products of the procedure are two updatable maps: the deformation activity map and the active deformation areas map. These maps present two different levels of information aimed at different levels of geohazard risk management, from a very simplified level of information to the classical deformation map based on SAR interferometry. The methodology has been successfully applied to La Gomera, Tenerife and Gran Canaria Islands (Canary Island archipelago). The main obtained results are discussed.

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Permanent Scatterer Interferometry (PSI) has been used to detect and characterize the subsidence of the Pisa urban area, which extends for 33 km 2 within the Arno coastal plain (Tuscany, Italy). Two SAR (Synthetic Aperture Radar) datasets, covering the time period from 1992 to 2010, were used to quantify the ground subsidence and its temporal evolution. A geotechnical borehole database was also used to make a correspondence with the detected displacements. Finally, the results of the SAR data analysis were contrasted with the urban development of the eastern part of the city in the time period from 1978 to 2013. ERS 1/2 (European Remote-Sensing Satellite) and Envisat SAR data, processed with the PSInSAR (Permanent Scatterer InSAR) algorithm, show that the investigated area is divided in two main sectors: the southwestern part, with null or very small subsidence rates (<2 mm/year), and the eastern portion which shows a general lowering with maximum deformation rates of 5 mm/year. This second area includes deformation rates higher than 15 mm/year, corresponding to small groups of buildings. The case studies in the eastern sector of the urban area have demonstrated the direct correlation between the age of construction of buildings and the registered subsidence rates, showing the importance of urbanization as an accelerating factor for the ground consolidation process.

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Abstract:In recent years, space-borne InSAR (interferometric synthetic aperture radar) techniques have shown their capabilities to provide precise measurements of Earth surface displacements for monitoring natural processes. Landslides threaten human lives and structures, especially in urbanized areas, where the density of elements at risk sensitive to ground movements is high. The methodology described in this paper aims at detecting terrain motions and building deformations at the local scale, by means of satellite radar data combined with in situ validation campaigns. The proposed approach consists of deriving maximum settlement directions of the investigated buildings from displacement data revealed by radar measurements and then in the cross-comparison of these values with background geological data, constructive features and on-field evidence. This validation permits better understanding whether or not the detected movements correspond to visible and effective damages to buildings. The method has been applied to the southwestern sector of Volterra (Tuscany region, Italy), which is a landslide-affected and partially urbanized area, through the use of COSMO-SkyMed satellite images as input data. Moreover, we discuss issues and possible misinterpretations when dealing with PSI (Persistent Scatterer Interferometry) data referring to single manufactures and the consequent difficulty of attributing the motion rate to ground displacements, rather than to structural failures.