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Underground mining is one of the human activities with the highest impact in terms of induced ground motion. The excavation of the mining levels creates pillars, rooms and cavities that can evolve in chimney collapses and sinkholes. This is a major threat where the mining activity is carried out in an urban context. Thus, there is a clear need for tools and instruments able to precisely quantify mining-induced deformation. Topographic measurements certainly offer very high spatial accuracy and temporal repeatability, but they lack in spatial distribution of measurement points. In the past decades, Multi-Temporal Satellite Interferometry (MTInSAR) has become one of the most reliable techniques for monitoring ground motion, including mining-induced deformation. Although with well-known limitations when high deformation rates and frequently changing land surfaces are involved, MTInSAR has been exploited to evaluate the surface motion in several mining area worldwide. In this paper, a detailed scale MTInSAR approach was designed to characterize ground deformation in the salt solution mining area of Saline di Volterra (Tuscany Region, central Italy). This mining activity has a relevant environmental impact, depleting the water resource and inducing ground motion; sinkholes are a common consequence. The MTInSAR processing approach is based on the direct integration of interferograms derived from Sentinel-1 images and on the phase splitting between low (LF) and high (HF) frequency components. Phase unwrapping is performed for the LF and HF components on a set of points selected through a "triplets closure" method. The final deformation map is derived by combining again the components to avoid error accumulation and by applying a classical atmospheric phase filtering to remove the remaining low frequency signal. The results obtained reveal the presence of several subsidence bowls, sometimes corresponding to sinkholes formed in the recent past. Very high deformation rates, up to −250 mm/yr, and time series with clear trend changes are registered. In addition, the spatial and temporal distribution of velocities and time series is analyzed, with a focus on the correlation with sinkhole occurrence. [ABSTRACT FROM AUTHOR]

• This study presents the analysis of the ground deformation measured using 26 years of satellite SAR data. • We investigated the driven factors of subsidence in a densely urbanized area. • Data retrieved by several boreholes and geotechnical investigations were used to model the building load and to validate remote sensing data. • The comparison between the consolidation curve and the time series suggests that SAR data can be used to evaluate the consolidation process. This paper shows the results of the comparison between Multi-temporal Synthetic Aperture Radar (MTInSAR) products derived from different sensors (C-band ERS 1/2, Envisat, Sentinel-1 and X-band COSMO-SkyMed) and geotechnical data to investigate the driving factors of subsidence which affect a freight terminal located along the a coastal plain of Tuscany (central Italy). MTInSAR data have been acquired in a very long period, between 1992 and 2018 and were analyzed in terms of subsidence rates and deformation time series at building scale. The obtained results show that the oldest buildings are still affected by a deformation rate close to −5 mm/yr, whereas recent buildings register rates around −40 mm/yr. Time series of deformation suggest that the deformation rates decrease over time following time-dependent trend that approximates the typical consolidation curve for compressible soils. The geotechnical and stratigraphical analysis of the subsurface data (boreholes, cone penetration tests and dilatometer tests) highlights the presence of a 15 m thick layer formed of clay characterized by poor geotechnical characteristics. The comparison among InSAR data, subsurface geological framework and geotechnical reconstruction suggests a possible evaluation of the timing of the primary and secondary consolidation processes. [ABSTRACT FROM AUTHOR]

Satellite interferometric data are widely exploited for ground motion monitoring thanks to their wide area coverage, cost efficiency and non-invasiveness. The launch of the Sentinel-1 constellation opened new horizons for interferometric applications, allowing the scientists to rethink the way in which these data are delivered, passing from a static view of the territory to a continuous streaming of ground motion measurements from space. Tuscany Region is the first worldwide example of a regional scale monitoring system based on satellite interferometric data. The processing chain here exploited combines a multi-interferometric approach with a time-series data mining algorithm aimed at recognizing benchmarks with significant trend variations. The system is capable of detecting the temporal changes of a wide variety of phenomena such as slow-moving landslides and subsidence, producing a high amount of data to be interpreted in a short time. Bulletins and reports are derived to the hydrogeological risk management actors at regional scale. The final output of the project is a list of potentially hazardous and accelerating phenomena that are verified on site by field campaign by completing a sheet survey in order to qualitatively estimate the risk and to suggest short-term actions to be taken by local entities. Two case studies, one related to landslides and one to subsidence, are proposed to highlight the potential of the monitoring system to early detect anomalous ground changes. Both examples represent a successful implementation of satellite interferometric data as monitoring and risk management tools, raising the awareness of local and regional authorities to geohazards. [ABSTRACT FROM AUTHOR]

Landslides are considered to be one of the main natural geohazards causing relevant economic damages and social effects worldwide. Italy is one of the countries worldwide most affected by landslides; in the Region of Tuscany alone, more than 100,000 phenomena are known and mapped. The possibility to recognize, investigate, and monitor these phenomena play a key role to avoid further occurrences and consequences. The number of applications of Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR) analysis for landslides monitoring and mapping greatly increased in the last decades thanks to the technological advances and the development of advanced processing algorithms. In this work, landslide-induced damage on structures recognized and classified by field survey and velocity of displacement re-projected along the steepest slope were combined in order to extract fragility curves for the hamlets of Patigno and Coloretta, in the Zeri municipality (Tuscany, northern Italy). Images using ERS1/2, ENVISAT, COSMO-SkyMed (CSK) and Sentinel-1 SAR (Synthetic Aperture Radar) were employed to investigate an approximate 25 years of deformation affecting both hamlets. Three field surveys were conducted for recognizing, identifying, and classifying the landslide-induced damage on structures and infrastructures. At the end, the damage probability maps were designed by means of the use of the fragility curves between Sentinel-1 velocities and recorded levels of damage. The results were conceived to be useful for the local authorities and civil protection authorities to improve the land managing and, more generally, for planning mitigation strategies. [ABSTRACT FROM AUTHOR]

The results of the continuous monitoring of ground deformation throughout the Tuscany region using radar images acquired by the Sentinel-1 satellite constellation of the European Space Agency (ESA) are presented here. This new monitoring approach, based on systematic imagery processing and analysis of deformation time series, is discussed at regional (for the entire Tuscany) and at local scale in the context of a case study of the Carpineta landslide, which is a large, active earth slide in the Northern Apennines (Pistoia province). The landslide registered an acceleration during the winter and spring of 2018 as a direct consequence of rainfall and snow melt. The increase in the deformation rate of the landslide, which led to the damage of several buildings, was promptly detected and monitored due to the enhanced temporal repetitiveness offered by the Sentinel-1 constellation. The results demonstrate that advances in satellite sensors, increases in computing capacity and the refinement of processing approaches and data screening tools can contribute to the development of new paradigms in satellite-based monitoring systems. Sentinel-1 data, which are systematically acquired with short revisiting times and then promptly processed, can now be used as a tool for the systematic tracking of ground deformation at the regional scale and for the continuous monitoring of slow and very slow landslides. [ABSTRACT FROM AUTHOR]

This work describes a new procedure aimed to semi-automatically identify clusters of active persistent scatterers and preliminarily associate them with different potential types of deformational processes over wide areas. This procedure consists of three main modules: (i) ADAfinder, aimed at the detection of Active Deformation Areas (ADA) using Persistent Scatterer Interferometry (PSI) data; (ii) LOS2HV, focused on the decomposition of Line Of Sight (LOS) displacements from ascending and descending PSI datasets into vertical and east-west components; iii) ADAclassifier, that semi-automatically categorizes each ADA into potential deformational processes using the outputs derived from (i) and (ii), as well as ancillary external information. The proposed procedure enables infrastructures management authorities to identify, classify, monitor and categorize the most critical deformations measured by PSI techniques in order to provide the capacity for implementing prevention and mitigation actions over wide areas against geological threats. Zeri, Campiglia Marittima–Suvereto and Abbadia San Salvatore (Tuscany, central Italy) are used as case studies for illustrating the developed methodology. Three PSI datasets derived from the Sentinel-1 constellation have been used, jointly with the geological map of Italy (scale 1:50,000), the updated Italian landslide and land subsidence maps (scale 1:25,000), a 25 m grid Digital Elevation Model, and a cadastral vector map (scale 1:5000). The application to these cases of the proposed workflow demonstrates its capability to quickly process wide areas in very short times and a high compatibility with Geographical Information System (GIS) environments for data visualization and representation. The derived products are of key interest for infrastructures and land management as well as decision-making at a regional scale. [ABSTRACT FROM AUTHOR]