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This work presents a sinkhole susceptibility and risk assessment mapping in Guidonia-Bagni di Tivoli plain (Italy), a travertine sinkhole-prone area where sudden occurrences of sinkholes have happened in past and recent times. We collected a point-like sinkhole inventory and we considered a series of different sinkholecontrolling and precursory factors over the study area, related to its geo-litho-hydrological setting and to its terrain deformational scenario, i.e. ground motion rates derived from InSAR COSMOSkyMed imagery. A sinkhole susceptibility map was produced through a machine learning model, namely Maximum Entropy algorithm (MaxEnt). Results highlight that the most determining factors for sinkhole formation are the lithology, the travertine thickness, groundwater and the land use. The sinkhole susceptibility map was then combined with data on vulnerability and elements-at-risk economic exposure in order to provide a sinkhole risk map of the area. The outcomes show that areas at higher risk covers about 2% of the total study area and primarily relies on the zoning of the main urban fabric. In particular, it is worth to highlight that 5% of the whole road-network pavement and 27% of all the residential buildings fall into High and Very High risk classes. Overall, results of this work demonstrate capabilities of machine learning models to assess sinkhole susceptibility for predicting potential sinkhole areas, and provide a sinkhole risk map, along with information on urban environment, as a useful tool for urban planning and geohazard risk management. [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]

The accurate evaluation of landslide-induced damage is a necessity for planning of proper and effective mitigation measures. It requires the implementation of field investigations to identify structural failures to more effectively trace landslide boundaries. Many methods have been proposed to classify landslide-induced damage of buildings. The existing methods demonstrate several advantages and drawbacks depending on the parameters considered, as lack of some important features and difficulties in applicability. A new classification approach of landslide-induced damage of facilities is proposed, which specifically focuses on assessing of damage degree and its relationship to the ground motion intensity and impact severity. The new approach is designed in two steps: a chart utilized during surveys to quantify cracks on structures and ground surface; ana posterioriranking of structures performed using a cell-grid matrix. Furthermore, a damage recording scheme useful for field surveying is proposed. This approach considers several parameters derived from different existing methodologies by smoothing out drawbacks and homogenizing the considered features. The resulting approach provides a new procedure of landslide-induced damage assessment adoptable in case of private dwellings, as it does not require internal accessibility, and it is exploitable for different landslide events and for different kinds of structures and facilities. [ABSTRACT FROM AUTHOR]

Landslide detection and mapping are essential issues for reducing impact of such natural disasters, and for improving the future built-up expansion and planning strategies, especially in developing countries where a reasonable land-use design is an important concern for sustainable growth and environmental management. Armenia is a landlocked country and its urban development is strongly tied to the improvement of infrastructures, which must takes into account the environmental setting and the slope instability of the area, in order to identify risks and possible damages to settlements and economic activities. The use of satellite-based Earth Observation data has advanced significantly in the last decade and has turned out to be very useful for measuring and monitoring slow-moving surface deformation phenomena with millimetric precision. In this framework, this study aims at providing a remote sensing-based Landslide Inventory Map (LIM) and a Landslide Susceptibility Map (LSM) over Dilijan (Armenia) area, performed within the Secondary Cities Urban Development in Armenia project. In particular, LIM and LSM in the study area were produced by using ground deformation measurements derived from satellite Synthetic Aperture Radar (SAR) data, acquired by ALOS and ENVISAT sensors from 2003 up to 2010, and integrated with photo-interpretation of recent optical images and morphological analysis of Digital Elevation Model (DEM). Given the extensive presence of vegetation in the area of interest, satellite SAR images were processed to produce both SqueeSAR™ and Temporary Coherent Scatterers data, which are PSI (Persistent Scatterer Interferometry) data conceived as evolution of PSInSAR™ approach and particularly suited for non-urban and rural areas characterized by low density of coherent terrain benchmarks over time. Landslide mapping produced through this work identifies the most hazardous landslide-affected and landslide-prone areas around Dilijan city, and can be used for further estimating environmental risks for urban infrastructure development in the area. [ABSTRACT FROM AUTHOR]

The evaluation of landslide specific risk, defined as the expected degree of loss due to landslides, requires the parameterization and the combination of a number of socio-economic and geological factors, which often needs the interaction of different skills and expertise (geologists, engineers, planners, administrators, etc.). The specific risk sub-components, i.e., hazard and vulnerability of elements at risk, can be determined with different levels of detail depending on the available auxiliary data and knowledge of the territory. These risk factors are subject to short-term variations and nowadays turn out to be easily mappable and evaluable through remotely sensed data and GIS (Geographic Information System) tools. In this work, we propose a qualitative approach at municipal scale for producing a "specific risk" map, supported by recent satellite PSI (Persistent Scatterer Interferometry) data derived from SENTINEL-1 C-band images in the spanning time 2014-2017, implemented in a GIS environment. In particular, PSI measurements are useful for the updating of a landslide inventory map of the area of interest and are exploited for the zonation map of the intensity of ground movements, needed for evaluating the vulnerability over the study area. Our procedure is presented throughout the application to the Volterra basin and the output map could be useful to support the local authorities with updated basic information required for environmental knowledge and planning at municipal level. Moreover, the proposed procedure is easily managed and repeatable in other case studies, as well as exploiting different SAR sensors in L- or X-band. [ABSTRACT FROM AUTHOR]

This work provides a multi-temporal and spatial investigation of landslide effects in the San Fratello area (Messina province within the Sicily region, Italy), by means of C-band and X-band Persistent Scatterer Interferometry (PSI) data, integrated with in situ field checks and a crack pattern survey. The Sicily region is extensively affected by hydrogeological hazards since several landslides regularly involved local areas across time. In particular, intense and catastrophic landslide phenomena have recently occurred in the San Fratello area; the last event took place in February 2010, causing large economic damage. Thus, the need for an accurate ground motions and impacts mapping and monitoring turns out to be significantly effective, in order to better identify active unstable areas and to help proper risk-mitigation measures planning. The combined use of historical and recent C-band satellites and current X-band Synthetic Aperture Radar sensors of a new generation permits spatially and temporally detection of landslide-induced motions on a local scale and to properly provide a complete multi-temporal evaluation of their effects on the area of interest. PSI ground motion rates are cross-compared with local failures and damage of involved buildings, recently recognized by in situ observations. As a result, the analysis of landslide-induced movements over almost 20 years and the validation of radar data with manufactured crack patterns, permits one to finally achieve a complete and reliable assessment in the San Fratello test site. [ABSTRACT FROM AUTHOR]

This work attempts to map recent land subsidence on the Sibari plain in Calabria region (Southern Italy), by exploiting vertical velocity values and time series of persistent scatterer interferometry (PSI) synthetic aperture radar (SAR) data acquired in the period 1992–2011 by different satellite systems. After reviewing other sources and rates of subsidence recorded by previous works since the beginning of the Holocene, this paper presents the spatial distribution of the current settlement rates showing that subsidence is due to the compressible alluvial sediments of the plain, but that in recent times it is mostly due also to human activities. In fact, according to the most recent monitoring period (2009–2011), downward motion rates are recorded as being only localized within site-specific industrial areas, such as the ‘Sibari Lakes’ nautical and residential centre and Corigliano Calabro Industrial Zone. The temporal analysis of persistent scatterers (PS) time series, carried out through the PS-Time program, adds further useful information, finally highlighting that, in these areas, subsidence has positively decreased or stabilized from the second semester of the year 2010. This work shows that PSI measurements provide support in the quantitative evaluation of known subsidence process and that the analysis of time series allows effective detection of the temporal evolution trends of the phenomenon, such as changes or deceleration in displacement rates, not otherwise visible by merely considering the average velocity. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM AUTHOR]

In this paper a methodology is proposed to elaborate landslide activity maps through the use of PS (Persistent Scatterer) data. This is illustrated through the case study of Tramuntana Range in the island of Majorca (Spain), where ALOS (Advanced Land Observing Satellite) images have been processed through a Persistent Scatterer Interferometry (PSI) technique during the period of 2007-2010. The landslide activity map provides, for every monitored landslide, an assessment of the PS visibility according to the relief, land use, and satellite acquisition parameters. Landslide displacement measurements are projected along the steepest slope, in order to compare landslide velocities with different slope orientations. Additionally, a ground motion activity map is also generated, based on active PS clusters not included within any known landslide phenomenon, but even moving, potentially referred to unmapped landslides or triggered by other kinds of geomorphological processes. In the Tramuntana range, 42 landslides were identified as active, four as being potential to produce moderate damage, intersecting the road Ma-10, which represents the most important road of the island and, thus, the main element at risk. In order to attest the reliability of measured displacements to represent landslide dynamics, a confidence degree evaluation is proposed. In this test site, seven landslides exhibit a high confidence degree, medium for 93 of them, and low for 51. A low confidence degree was also attributed to 615 detected active clusters with a potential to cause moderate damage, as their mechanism of the triggering cause is unknown. From this total amount, 18 of them intersect the Ma-10, representing further potentially hazardous areas. The outcomes of this work reveal the usefulness of landslide activity maps for environmental planning activities, being exportable to other radar data and different geomorphological settings. [ABSTRACT FROM AUTHOR]

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 14 km 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 ±5 mm/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 (16 mm/year) is reduced by ~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. [ABSTRACT FROM AUTHOR]

Multi-Temporal Satellite Interferometry (MTInSAR) is gradually evolving from being a tool developed by the scientific community exclusively for research purposes to a real operational technique that can meet the needs of different users involved in geohazard mitigation. This work aims at showing the innovative operational use of satellite radar interferometric products in Civil Protection Authority (CPA) practices for monitoring slow-moving landslides. We present the example of the successful ongoing monitoring system in the Valle D'Aosta Region (VAR-Northern Italy). This system exploits well-combined MTInSAR products and ground-based instruments for landslide management and mitigation strategies over the whole regional territory. Due to the critical intrinsic constraints of MTInSAR data, a robust regional satellite monitoring integrated into CPA practices requires the support of both in situ measurements and remotely sensed systems to guarantee the completeness and reliability of information. The monitoring network comprises three levels of analysis: Knowledge monitoring, Control monitoring, and Emergency monitoring. At the first monitoring level, MTInSAR data are used for the preliminary evaluation of the deformation scenario at a regional scale. At the second monitoring level, MTInSAR products support the prompt detection of trend variations of radar benchmarks displacements with bi-weekly temporal frequency to identify active critical situations where follow-up studies must be carried out. In the third monitoring level, MTInSAR data integrated with ground-based data are exploited to confirm active slow-moving deformations detected by on-site instruments. At this level, MTInSAR data are also used to carry out back analysis that cannot be performed by any other tool. From the example of the Valle D'Aosta Region integrated monitoring network, which is one of the few examples of this kind around Europe, it is evident that MTInSAR provides a great opportunity to improve monitoring capabilities within CPA activities. [ABSTRACT FROM AUTHOR]

The continuous monitoring of displacements occurring on the Earth surface by exploiting MTInSAR (Multi Temporal Interferometry SAR) Sentinel-1 data is a solid reality, as testified by the ongoing operational ground motion service in the Tuscany region (Central Italy). In this framework, anomalies of movement, i.e., accelerations or deceleration as seen by the time series of displacement of radar targets, are identified. In this work, a Machine Learning algorithm such as the Random Forest has been used to assess the probability of occurrence of the anomalies induced by slope instability and subsidence. About 20,000 anomalies (about 7000 and 13,000 for the slope instability and the subsidence, respectively) were collected between 2018 and 2020 and were used as input, while ten different variables were selected, five related to the morphological and geological setting of the study area and five to the radar characteristics of the data. The resulting maps may provide useful indications of where a sudden change of displacement trend may occur, analyzing the contribution of each factor. The cross-validation with the anomalies collected in a following timespan (2020–2021) and with official landslide and subsidence inventories provided by the regional authority has confirmed the reliability of the final maps. The adoption of a map for assessing the probability of the occurrence of MTInSAR anomalies may serve as an enhanced geohazard prevention measurement, to be periodically updated and refined in order to have the most precise knowledge possible of the territory. [ABSTRACT FROM AUTHOR]

• Satellite interferometric data as tools for landslide intensity estimation. • Intensity as input for landslide potential loss calculation. • Regional scale approach fully relying on interferometric data. • Combination of interferometric data and gravitational process models. Multi-Temporal Interferometric Synthetic Aperture Radar (MTInSAR) data offer a valuable support to landslide mapping and to landslide activity estimation in mountain environments, where in situ measures are sometimes difficult to gather. Nowadays, the interferometric approach is more and more used for wide-areas analysis, providing useful information for risk management actors but at the same time requiring a lot of efforts to correctly interpret what satellite data are telling us. In this context, hot-spot-like analyses that select and highlight the fastest moving areas in a region of interest, are a good operative solution for reducing the time needed to inspect a whole interferometric dataset composed by thousands or millions of points. In this work, we go beyond the concept of MTInSAR data as simple mapping tools by proposing an approach whose final goal is the quantification of the potential loss experienced by an element at risk hit by a potential landslide. To do so, it is mandatory to evaluate landslide intensity. Here, we estimate intensity using Active Deformation Areas (ADA) extracted from Sentinel-1 MTInSAR data. Depending on the localization of each ADA with respect to the urban areas, intensity is derived in two different ways. Once exposure and vulnerability of the elements at risk are estimated, the potential loss due to a landslide of a given intensity is calculated. We tested our methodology in the Eastern Valle d'Aosta (north-western Italy), along four lateral valleys of the Dora Baltea Valley. This territory is characterized by steep slopes and by numerous active and dormant landslides. The goal of this work is to develop a regional scale methodology based on satellite radar interferometry to assess the potential impact of landslides on the urban fabric. [ABSTRACT FROM AUTHOR]

This study aimed at evaluating and mapping Ground Subsidence Susceptibility (GSS) in the Grosseto plain (Tuscany Region, Italy) by exploiting multi-temporal satellite InSAR data and by applying two parallel approaches; a bivariate statistical analysis (Frequency Ratio) and a mathematical probabilistic model (Fuzzy Logic operator). The Grosseto plain experienced subsidence and sinkholes due to natural causes in the past and it is still suffering slow-moving ground lowering. Five conditioning subsidence-related factors were selected and managed in a GIS environment through an overlay pixel-by-pixel analysis. Firstly, multi-temporal ground subsidence inventory maps were prepared in the study area by starting from two inventories referred to distinct temporal intervals (2003–2009 and 2014–2019) derived from Persistent Scatterers Interferometry (PSI) data of ENVISAT and SENTINEL-1 satellites. Then, the susceptibility modelling was performed through the Frequency Ratio (FR) and Fuzzy Logic (FL) approaches. These analyses led to slightly different scenarios which were compared and discussed. Results show that flat areas on alluvial and colluvial deposits with thick sedimentary cover (higher than 20 m) on the bedrock in the central and eastern sectors of the plain are the most susceptible to land subsidence. The obtained FR- and FL-based GSS maps were finally validated with a ROC (Receiver Operating Characteristic) analysis, in order to estimate the overall performance of the models. The AUC (Area Under Curve) values of ROC analysis of the FR model were higher than the ones of FL model, suggesting that the former is a better and more appropriate predictor for subsidence susceptibility analysis in the study area. In conclusion, GSS maps provided a qualitative overview of the subsidence scenarios and may be helpful to predict and preliminarily identify high-risk areas for environmental local authorities and decision makers in charge of land use planning in the study area. Finally, the presented methodologies to derive GSS maps are easily reproducible and could also be applied and tested in other test sites worldwide, in order to check the modeling performance in different environmental settings. [ABSTRACT FROM AUTHOR]

The complex landslide of Agnone, located in Molise Region (southern Italy), is a large deep-seated roto-translational slide, involving terrigenous flysch sequences and evolving in the lower portion, in an earth flow. First evidences of landslide activities date back to early 1900s and keep on moving in several time spans up to nowadays. This work illustrates the contribution of multiple optical and radar remote sensing data to landslide investigation approximately across a century as well as to mapping and monitoring ground displacements at the catchment scale.In particular, we firstly revised information from scientific literature and technical reports, compiling monitoring data acquired through inclinometers and geo-morphological surveys in preceding studies to characterize the geological setting of the area. Additionally, we used GPS data acquired from 2010 to 2015 to monitor ground surface motions on some benchmarks of the area. Then, we exploited remotely-sensed data in order to in-depth investigate the spatial and temporal evolution of the landslide-affected catchment.The use of historical air-photos enabled the generation of 3D models by means of the Structure for Motion (SfM) technique to detect, map and monitor unique geomorphological landscapes across several decades. Historical and recent sets of optical photographs from 1945 to 2003 were used in the study area to perform 3D reconstructions and analyze the geomorphological enlargement of the Agnone landslide over 60 years. Radar satellite images acquired by ERS1/2 and ENVISAT constellations at medium spatial resolution, in the spanning time 1992-2010, and by COSMO-SkyMed at high resolution, covering the period 2012-2015, were processed through Persistent Scatterer Interferometry (PSI) techniques. The derived PSI data provided yearly velocities and time series of ground deformation with millimetric accuracy and were exploited for back-monitoring slow surface displacements and for better tracing the boundaries of the mass movement. All data were discussed and used to increase the knowledge about the ground motions affecting the whole Agnone landslide and the surrounding territory. Remotely-sensed data were also compared through in situ field checks to evaluate landslide-induced damage on structures and infrastructures within and close to the landslide body. Outcomes of these analyses demonstrated the operative usefulness of the combination of multi-temporal and multi-technique conventional and remote sensing data for the assessment of spatial and temporal evolution of landslides at basin scale. Moreover, the collected data allowed to plan countermeasures and mitigation actions on the Agnone area according to the distribution and intensity of the detected landslide hazard. [ABSTRACT FROM AUTHOR]

In the last decade satellite remote sensing has become an effective tool for monitoring geo-hazard-induced ground motions, and has been increasingly used by the scientific community. Direct and indirect costs due to geo-hazards are currently rising, causing serious socio-economics and casualty losses. Therefore, creating a priority list turns out to be essential to highlight the most relevant ground deformations and to better focus risk management practices at regional scale. The Sentinel-1 constellation, thanks to the 6-days repeatability and the free availability of the data, allows to easily update the geo-hazard-induced ground motions, compared to other kind of satellite sensors. In this work, a hot-spot-like method is presented by filtering a large stack of Sentinel-1 images processed by means of the SqueeSAR algorithm. Three periods, with six months repetitiveness, have been analysed in order to evaluate the behaviour and evolution of deformation clusters. The target area is Tuscany Region, located in the central part of Italy and affected by a wide gamma of geohazards, ranging from landslides to large subsidence areas. The final output is a geo-database of ground motions that can be used by regional authorities to prioritize and to effectively plan local risk reduction actions. [ABSTRACT FROM AUTHOR]

Landslides are among the most important and frequent natural calamities that cause severe socio-economic and human losses. After earthquakes, landslides are responsible for the greatest number of casualties and the largest amount of damage to man-made structures. On average, southern Italy is affected by a high spatial density of landslides due to its complex geological setting, which often predisposes it to slope instability phenomena under both natural and anthropogenic influences. Structurally complex formations are widespread in the southern Apennines and are characterized by high heterogeneity and very poor mechanical properties. Thus, these formations represent one of the main factors contributing to the predisposition of slopes to landsliding. In this paper, landslide-induced damage was investigated and analyzed in an area within the municipality of Agnone (Molise region), which is affected by a complex landslide that involves a structurally complex formation. The approaches used were based on six different methods that have previously been described in the literature, and a comparison of the results was made. Data regarding the damage, which consists largely of cracks observed in buildings and at the ground, were compiled through field surveys. The results were critically analyzed to note the advantages and constraints of each classification scheme. The aim of the work was to apply and compare different approaches in order to test the best and most accurate procedures for assessing damage due to landslides at the scale of individual buildings as well as to provide an objective assessment of the degree of landslide damage to structures and facilities. [ABSTRACT FROM AUTHOR]

A 1:10,000 scale landslide inventory map has been prepared for the area between the Furiano and Rosmarino creeks, in the Nebrodi Mountains (north-eastern Sicily, Italy), a territory highly prone to slope failures, due to the local geological and geomorphological settings and intense rainfall. The landslide inventory database included within the Hydrogeological Setting Plan of the Sicily Region has been used as a starting point for this work. The updated inventory map has been compiled through a combination of conventional approaches (i.e. aerial photo-interpretation and field surveys) and new remote sensing techniques (ground deformation measurements obtained by interferometric analysis of satellite Synthetic Aperture Radar images). The new landslide inventory consists of 566 events, classified according to their typology and state of activity. [ABSTRACT FROM PUBLISHER]

Volterra (Central Italy) is a town of great historical interest, due to its vast and well-preserved cultural heritage, including a 2.6 km long Etruscan-medieval wall enclosure representing one of the most important elements. Volterra is located on a clayey hilltop prone to landsliding, soil erosion, therefore the town is subject to structural deterioration. During 2014, two impressive collapses occurred on the wall enclosure in the southwestern urban sector. Following these events, a monitoring campaign was carried out by means of remote sensing techniques, such as space-borne (PS-InSAR) and ground-based (GB-InSAR) radar interferometry, in order to analyze the displacements occurring both in the urban area and the surrounding slopes, and therefore to detect possible critical sectors with respect to instability phenomena. Infrared thermography (IRT) was also applied with the aim of detecting possible criticalities on the wall-enclosure, with special regards to moisture and seepage areas. PS-InSAR data allowed a stability back-monitoring on the area, revealing 19 active clusters displaying ground velocity higher than 10 mm/year in the period 2011-2015. The GB-InSAR system detected an acceleration up to 1.7 mm/h in near-real time as the March 2014 failure precursor. The IRT technique, employed on a double survey campaign, in both dry and rainy conditions, permitted to acquire 65 thermograms covering 23 sectors of the town wall, highlighting four thermal anomalies. The outcomes of this work demonstrate the usefulness of different remote sensing technologies for deriving information in risk prevention and management, and the importance of choosing the appropriate technology depending on the target, time sampling and investigation scale. In this paper, the use of a multi-platform remote sensing system permitted technical support of the local authorities and conservators, providing a comprehensive overview of the Volterra site, its cultural heritage and landscape, both in near-real time and back-analysis and at different scales of investigation. [ABSTRACT FROM AUTHOR]

The Italian vessel Costa Concordia wrecked on January 13th 2012 offshore the Giglio Island (Tuscany, Italy), with the loss of 32 lives. Salvage operation of the vessel started immediately after the wreck. This operation was the largest and most expensive maritime salvage ever attempted on a wrecked ship and it ended in July 2014 when the Costa Concordia was removed from the Giglio Island, and dragged in the port of Genoa where it was dismantled. The refloating and removal phases of the Costa Concordia were monitored, in the period between 14th and 27th of July, exploiting SAR (Synthetic Aperture Radar) images acquired by the X-band COSMO-SkyMed satellite constellation in crisis mode. The main targets of the monitoring system were: (i) the detection of possible spill of pollutant material from the vessel and (ii) to exclude that oil slicks, illegally produced by other vessels, could be improperly linked to the naval convoy during its transit along the route between the Giglio Island and the port of Genoa. Results point out that the adopted monitoring system, through the use of the COSMO-SkyMed constellation, can be profitably employed to monitor emergency phases related to single ship or naval convoy over wide areas and with a suitable temporal coverage. Furthermore, the refloating and removal phases of the Costa Concordia were a success because no pollution was produced during the operations. [ABSTRACT FROM AUTHOR]

Landslide geodatabases, including inventories and thematic data, today are fundamental tools for national and/or local authorities in susceptibility, hazard and risk management. A well organized landslide geo-database contains different kinds of data such as past information (landslide inventory maps), ancillary data and updated remote sensing (space-borne and ground based) data, which can be integrated in order to produce landslide susceptibility maps, updated landslide inventory maps and hazard and risk assessment maps. Italy is strongly affected by landslide phenomena which cause victims and significant economic damage to buildings and infrastructure, loss of productive soils and pasture lands. In particular, the Messina Province (southern Italy) represents an area where landslides are recurrent and characterized by high magnitude, due to several predisposing factors (e.g. morphology, land use, lithologies) and different triggering mechanisms (meteorological conditions, seismicity, active tectonics and volcanic activity). For this area, a geodatabase was created by using different monitoring techniques, including remote sensing (e.g. SAR satellite ERS1/2, ENVISAT, RADARSAT-1, TerraSAR-X, COSMO-SkyMed) data, and in situ measurements (e.g. GBInSAR, damage assessment). In this paper a complete landslide geodatabase of the Messina Province, designed following the requirements of the local and national Civil Protection authorities, is presented. This geo-database was used to produce maps (e.g. susceptibility, ground deformation velocities, damage assessment, risk zonation) which today are constantly used by the Civil Protection authorities to manage the landslide hazard of the Messina Province. [ABSTRACT FROM AUTHOR]

Buildings are sensitive to movements caused by ground deformation. The mapping both of spatial and temporal distribution, and of the degree of building damages represents a useful tool in order to understand the landslide evolution, magnitude and stress distribution. The high spatial resolution of space-borne SAR interferometry can be used to monitor displacements related to building deformations. In particular, PSInSAR technique is used to map and monitor ground deformation with millimeter accuracy. The usefulness of the above mentioned methods was evaluated in San Fratello municipality (Sicily, Italy), which was historically affected by landslides: the most recent one occurred on 14th February 2010. PSInSAR data collected by ERS 1/2, ENVISAT, RADARSAT-1 were used to study the building deformation velocities before the 2010 landslide. The X-band sensors COSMO-SkyMed and TerraSAR-X were used in order to monitor the building deformation after this event. During 2013, after accurate field inspection on buildings and structures, damage assessment map of San Fratello were created and then compared to the building deformation velocity maps. The most interesting results were obtained by the comparison between the building deformation velocity map obtained through COSMO-SkyMed and the damage assessment map. This approach can be profitably used by local and Civil Protection Authorities to manage the post-event phase and evaluate the residual risks. [ABSTRACT FROM AUTHOR]

Velocity is one of the most important parameters to evaluate the damaging potential of a mass movement, but its assessment, especially for extremely rapid landslides, is a complex task. In the literature, several models to assess mass movement velocity exist, but they usually require many detailed parameters, and therefore, they are applicable only to a single slope and not usable for regional-scale analyses. This study aims to propose a simple morphometric methodology, based on the spatialisation of the Energy Line method, to determine the velocity of shallow landslides and rockfalls at a regional scale. The proposed method requires a limited amount of input data (landslide perimeters and a digital elevation model), and its application can be carried out using GIS software and a Matlab code. The test area of this work is the Valle d'Aosta Region (Northern Italy), selected due to its peculiar geological and geomorphological setting that makes this region susceptible to the occurrence of both shallow landslides and rockfalls. Since measured velocity values for rockfalls and shallow landslides were not available, the results obtained with the proposed method have been validated through the implementation of a model in the literature, namely the Gravitational Process Path (GPP) model, for some selected landslides. [ABSTRACT FROM AUTHOR]

In this work, we present a methodology for improving persistent scatterer interferometry (PSI) data analysis for landslide studies. This methodology is a revision of previously described procedures with several improved and newly proposed aspects. To both evaluate and validate the results from this methodology, we used various persistent scatterer (PS) datasets from different satellites (ERS – ENVISAT, Radarsat, TerraSAR-X, and ALOS PALSAR) that were processed using three PSI techniques (stable point network – SPN, permanent scatterer interferometry – PSInSAR™, and SqueeSAR™) to map and monitor landslides in various mountainous environments in Spain and Italy. This methodology consists of a preprocessing model that predicts the presence of a PS over a certain area and a post-processing method used to determine the stability threshold, project the line of sight (LOS) velocity along the slope, estimate the E–W and vertical components of the velocity, and identify anomalous areas. [ABSTRACT FROM PUBLISHER]

The Global Navigation Satellite System (GNSS) and Synthetic Aperture Radar Interferometry (InSAR) can be combined to achieve different goals, owing to their main principles. Both enable the collection of information about ground deformation due to the differences of two consequent acquisitions. Their variable applications, even if strictly related to ground deformation and water vapor determination, have encouraged the scientific community to combine GNSS and InSAR data and their derivable products. In this work, more than 190 scientific contributions were collected spanning the whole European continent. The spatial and temporal distribution of such studies, as well as the distinction in different fields of application, were analyzed. Research in Italy, as the most represented nation, with 47 scientific contributions, has been dedicated to the spatial and temporal distribution of its studied phenomena. The state-of-the-art of the various applications of these two combined techniques can improve the knowledge of the scientific community and help in the further development of new approaches or additional applications in different fields. The demonstrated usefulness and versability of the combination of GNSS and InSAR remote sensing techniques for different purposes, as well as the availability of free data, EUREF and GMS (Ground Motion Service), and the possibility of overcoming some limitations of these techniques through their combination suggest an increasingly widespread approach. [ABSTRACT FROM AUTHOR]

The 6-days repeatability of Sentinel-1 constellation allows building up an interferometric stack with unprecedented velocity. Easily updatable hot-spot analyses, frequently repeated following the update of Sentinel-1 images, represent very useful tools for MTInSAR (Multi-Temporal Interferometric Synthetic Aperture Radar) data analysis. Mountain regions are a challenging environment for interferometric analyses because of their climatic, morphological and land cover characteristics. In this context, MTInSAR data can retrieve reliable information over wide areas, with high cost-benefits ratio and where the installation of ground-based devices is not feasible. Considering the well-known limitations of interferometric techniques (such as fast motions or temporal and spatial decorrelation), hot-spot analyses are a viable solution for semi-automatic ground movements extraction over mountain regions. In this work, we present an example of a hot-spot analysis applied to a large stack of MTInSAR products generated by means of SqueeSAR technique over an alpine region (Valle d'Aosta, north-western Italy). The obtained outputs allow detecting 277 moving areas connected to landslides and mass wasting processes in general. These products are intended to be implemented in the landslide risk management chain of the region, focusing on landslide state of activity definition and landslide mapping. [ABSTRACT FROM AUTHOR]

In many landslide studies, the possibility to predict future behaviour is still a major concern. The most popular methods to achieve this prediction rely on the analysis of monitoring data of displacement for the detection of accelerating areas, as they can directly related to precursory movements that typically precede collapse. Methods deducing reliable failure predictions have been largely applied at local scale, where in situ monitoring systems can be installed. So far, the lack of systematic information on ground displacement acquired at regional scale was a serious limit hampering the application of failure prediction methods at wide scale. Such limitations can be partially solved through the exploitation of spaceborne platforms. Despite this, the low data sampling frequency of most of the satellite systems hampered the possibility to retrieve the necessary details of tertiary creep characterized by accelerating deformation.The launch of Sentinel-1 mission opened a new opportunity for InSAR monitoring applications thanks to the increased acquisition frequency, the regularity of acquisitions and the policy on data access. The potential of the Sentinel-1 for the detection of pre-failure accelerating creep has been recently proved through some retrospective InSAR analysis. For instance, the post-event application of the Fukuzono method to the Sentinel-1 deformation time series of the catastrophic Maoxian landslide (China), occurred on 24 June 2017, pointed out that an accurate estimation of the time of collapse was already possible at the begin of June.Despite the operational readiness of the Sentinel-1 constellation, most of the applications so far have been aimed at assessing the use of this data source to spot unstable areas or to capture pre-failure signs after major collapse, rather than providing new streamlines of information for monitoring solutions. We provide an example of the potential of multi-temporal InSAR analyses applied to Sentinel-1 data for continuous monitoring of ground deformation induced by hydrogeological processes. We exploit Sentinel-1 images to implement an operational service based on advanced interferometric products suitable for risk mitigation at the regional scale. This service relies on the systematic processing of Sentinel-1 images to create continuously updated ground deformation data. In fact, as soon as a new acquisition is available, the new image is used to update all displacement time series of all measurement points identified in the area of interest. Time series are then automatically analysed through a post-processing procedure, highlighting any anomalous trends and/or acceleration affecting the area of interest and providing possible alerts.We present and discuss this monitoring system through the case study of the Tuscany and Valle d'Aosta Region (Italy), specifically selected due to their peculiar geological settings, highly prone to slope instability phenomena. These results show that satellite radar data, systematically acquired over large areas with short revisiting time, could be used not only for mapping unstable areas, but also for actual landslide warning, at least for some typologies of sliding phenomena. This means that the transition from historical analysis of ground deformation to a continuous monitoring with prediction capabilities at regional scale using satellite radar data is now possible. [ABSTRACT FROM AUTHOR]

The investigation of large landslides in high alpine environments is often hindered by the difficult accessibility of the mountainous terrain. Efforts are typically concentrated on the remote measurement of the surface displacements, in order to define the general slope dynamics and identify phases of increasing activity. The characterization of such phenomena is challenging, due to their complex nature as well as the limitations of monitoring techniques. Appropriately integrating monitoring data from different sources can help reduce uncertainties, yet it is seldom done. In this paper, the outcomes of GNSS, satellite InSAR, and GBInSAR campaigns performed at the Bosmatto landslide (Northwestern Alps, Italy) are presented. The joint analysis provided a comprehensive view of the deformation field of the landslide, which revealed a gradually decreasing dip angle of the calculated movement vectors from head to toe. The instability was interpreted as a 2.5 – 3.5 ∗ 106 m3 rockslide, moving at peak velocities >50 mm/y according to a broadly roto-translational mechanism. The impact of the seasonal snow cover on the reliability of the interferometric acquisitions was also evaluated. Advantages and implications offered by the combination of multiple monitoring techniques are highlighted. • The Bosmatto landslide is a large instability in a steep alpine slope. • Site investigation is challenging because of the hardly accessible terrain. • Joint analysis of GNSS, satellite InSAR, and GBInSAR remote sensing data • The general mechanism and behavior of the landslide are determined. • Implications for the monitoring of large landslides in high alpine environments [ABSTRACT FROM AUTHOR]

In this manuscript, an integrated strategy that exploits both phase and amplitude features of satellite SAR (synthetic aperture radar) images and ground data is proposed for deriving the deformation field induced by a complex landslide that affected part of the village of Ponzano (Abruzzi Region, Central Italy). The February 12, 2017, landslide was triggered by the combined effects of intense rainfalls and snowmelt that saturated the slope. The SqueeSAR algorithm was applied to two C-band SAR datasets, composed by Radarsat-2 and Sentinel-1 images, spanning a nine-year time interval before the landslide occurrence. Moreover, the amplitude information carried by two TerraSAR-X images, acquired immediately before and after the event, was exploited to derive the total displacement generated by the landslide movement by means of the RMT (rapid motion tracking) algorithm. The obtained results allow describing the landslide behavior before and after its failure. In particular, the back-monitoring analysis shows that the landslide was already slowly moving, with deformation rates increasing from the Radarsat-2 to the Sentinel-1 monitored periods, 10 years before its complete mobilization. The landslide failure of February 2017 produced maximum displacements of about 10 m in some sectors of the affected area. The registered deformation rates and the localization of the maximum displacements areas were confirmed by field data, collected during a field campaign and a helicopter recognizance of the damaged areas, both performed after the event. [ABSTRACT FROM AUTHOR]

The detection of active movements that could threat the infrastructures and the population is one of the main priorities of the risk management chain. Interferometric Synthetic Aperture Radar (InSAR) techniques represent one of the most useful answers to this task; however, it is difficult to manage the huge amount of information derived from the interferometric analysis. In this work, we present a procedure for deriving impact assessment maps, over a regional test site, using as starting point Sentinel-1 SAR (Synthetic Aperture Radar) images and a catalogue of elements at risk that acts as a second input of the methodology. We applied the proposed approach, named as Vulnerable Elements Activity Maps (VEAM), to the islands of Gran Canaria, La Gomera and Tenerife (Spain), where we analysed SAR images covering the time interval November 2014-September 2016. The methodology, meant to be a powerful tool for reducing the time needed for a complete analysis of a full stack of InSAR data, is ideally suited for Civil Protection Authorities. The application of the methodology allowed to detect 108 areas affected by active deformation that are threatening one or more elements at risk in 25 municipalities of the three islands. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

In this study, we present the detection and characterization of ground displacements in the urban area of Pisa (Central Italy) using Interferometric Synthetic Aperture Radar (InSAR) products. Thirty RADARSAT-2 and twenty-nine COSMO-SkyMed images have been analyzed with the Small BAseline Subset (SBAS) algorithm, in order to quantify the ground subsidence and its temporal evolution in the three-year time interval from 2011 to 2014. A borehole database was reclassified in stratigraphical and geotechnical homogeneous units, providing the geological background needed for the local scale analysis of the recorded displacements. Moreover, the interferometric outputs were compared with the last 30 years' urban evolution of selected parts of the city. Two deformation patterns were recorded by the InSAR data: very slow vertical movements within the defined stability threshold (-2.5 mm/yr) and areas with subsidence rates down to -5 to -7 mm/yr, associated with high peak velocities (-15 to -20 mm/yr) registered by single buildings or small groups of buildings. Some of these structures are used to demonstrate that the high subsidence rates are related to the recent urbanization, which is the trigger for the accelerated consolidation process of highly compressible layers. Finally, this urban area was a valuable test site for demonstrating the different results of the C- and X-band data processing, in terms of the density of points and the quality of the time series of deformation. [ABSTRACT FROM AUTHOR]

This paper includes a critical review of the existing literature on the use of satellite SAR imagery for subsidence analysis. Land subsidence, related to multiple natural and human-induced processes, is observed globally in an increasing number of areas. Potentially leading to severe impacts on economics and the environment, subsidence has attracted growing scientific attention and, over the last decades, new tools and methods have been developed for accurately measuring the spatial and temporal evolution of surface deformations associated with subsidence phenomena. The collection of the existing scientific literature on the satellite InSAR for subsidence analysis was conducted in January 2022 exploiting the WoS's freely accessible web search engine. An extensive database of 1059 scientific contributions was compiled, covering the period 1997–2021. The content of each record in the literature database has been critically examined to collect and store information regarding the study area location, microwave band adopted, satellite used, processing approach, subsidence cause, application type, field evidence and strategies to validate and compare InSAR data. Analysis of temporal distribution revealed a substantial growth in scientific production and an increasing interest of geoscientists, with a mean value of 21 articles per year from 1997 to 2014, rising to about 100 articles per year between 2015 and 2021. All continents include at least a study area, with Asia and Europe having the largest number of case studies, with 586 and 281 analyses in their territory, respectively, and revealing a clear geographical bias in subsidence study locations. Graphical visualizations and syntheses of current applications are presented. The large availability of different acquisition bands, the increasing imaging capabilities, refinement of processing approaches, and growing expertise in data interpretation allowed InSAR data to be used at different scales of analysis, for different purposes and subsidence types, in a wide range of physiographic settings. This review highlights that satellite InSAR has moved from being a niche topic to an operative tool with a major role in subsidence studies. Despite more than 25 years of progress and advancements, technical and operational challenges remain to be faced. Leveraging on the analysis of the literature review and authors' experience, recommendations and perspectives are provided for a more effective use of InSAR data. [ABSTRACT FROM AUTHOR]

The spatial resolution of digital elevation models (DEMs) is an important factor for reliable landslide studies. Multi-interferometric techniques such as persistent scatterer interferometric synthetic aperture radar (PSInSAR) are used to evaluate the landslide state of activity and its ground deformation velocity, which is commonly measured along the satellite line of sight (LOS). In order to compare velocities measured by different satellites in different periods, their values can be projected along the steepest slope direction, which is the most probable direction of real movement. In order to achieve this result, DEM-derived products are needed. In this paper, the effectiveness of different DEM resolutions was evaluated in order to project ground deformation velocities measured by means of PSInSAR technique in two different case studies in the Messina Province (Sicily, southern Italy): San Fratello and Giampilieri. Three DEMs were used: (i) a 20-m resolution DEM of the Italian Military Geographic Institute (IGM), (ii) a 2-m resolution DEM derived from airborne laser scanning (ALS) light detection and ranging (LiDAR) data for the San Fratello 2010 landslide, and (iii) a 1-m resolution DEM derived from ALS LiDAR data for the area of Giampilieri. The evaluation of the applied method effectiveness was performed by comparing the DEMs elevation with those of each single permanent scatterer (PS) and projecting the measured velocities along the steepest slope direction. Results highlight that the higher DEM resolution is more suitable for this type of analysis; in particular, the PS located nearby the watershed divides is affected by geometrical problems when their velocities are projected along the steepest slope. [ABSTRACT FROM AUTHOR]

Permanent Scatterer Interferometry (PSI) has been used to detect and characterize the subsidence of the Pisa urban area, which extends for 33 km² 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. [ABSTRACT FROM AUTHOR]

In the last few years several advances have been made in the use of radar images to detect map monitor ground deformations. DInSAR (Differential Synthetic Aperture Radar Interferometry) A-DInSAR/PSI (Advanced DInSAR/Persistent Scatterers Interferometry) technologies have been successfully applied in the study of deformation phenomena induced by for example active tectonics volcanic activity ground water exploitation mining landslides both at local regional scales. In this paper the existing European Space Agency (ESA) archives (acquired as part of the FP -DORIS project) which were collected by the ERS- / ENVISAT satellites operating in the microwave C-band were analyzed exploited to understand the dynamics of landslide subsidence phenomena. In particular this paper presents the results obtained as part of the FP -DORIS project to demonstrate that the full exploitation of very long deformation time series (more than years) can play a key role in understanding the dynamics of natural human-induced hazards. [ABSTRACT FROM AUTHOR]

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]

Identification and classification of landslides is a preliminary and crucial work for landslide risk assessment and hazard mitigation. The exploitation of surface deformation velocity derived from satellite synthetic aperture radar interferometry (InSAR) is a consolidated and suitable procedure for the recognition of active landslides over wide areas. However, the calculated displacement velocity from InSAR is one-dimensional motion along the satellite line of sight (LOS), representing a major hurdle for landslide type and failure mechanism classification. In this paper, different velocity datasets derived from both ascending and descending Sentinel-1 data are employed to analyze the surface ground movement of the Huangshui region (Northwestern China). With global warming, precipitation in the Huangshui region, geologically belonging to the loess basin in the eastern edge of Qing-Tibet Plateau, has been increasing, often triggering a large number of landslides, posing a potential threat to local citizens and natural and anthropic environments. After processing both SAR data geometries, the surface motion was decomposed to obtain the two-dimensional displacements (vertical and horizontal E–W). Thus, a classification criterion of the loess landslide types and failure mode is proposed, according to the analysis of deformation direction, velocities, texture, and topographic characteristics. With the support of high-resolution images acquired by remote sensing and unmanned aerial vehicle (UAV), 14 translational slides, seven rotational slides, and 10 loess flows were recognized in the study area. The derived results may provide solid support for stakeholders to comprehend the hazard of unstable slopes and to undertake specific precautions for moderate and slow slope movements. [ABSTRACT FROM AUTHOR]

Landslides recurrently impact the Italian territory, producing huge economic losses and casualties. Because of this, there is a large demand for monitoring tools to support landslide management strategies. Among the variety of remote sensing techniques, Interferometric Synthetic Aperture Radar (InSAR) has become one of the most widely applied for landslide studies. This work reviews a variety of InSAR-related applications for landslide studies in Italy. More than 250 papers were analyzed in this review. The first application dates back to 1999. The average production of InSAR-related papers for landslide studies is around 12 per year, with a peak of 37 papers in 2015. Almost 70% of the papers are written by authors in academia. InSAR is used (i) for landslide back analysis (3% of the papers); (ii) for landslide characterization (40% of the papers); (iii) as input for landslide models (7% of the papers); (iv) to update landslide inventories (15% of the papers); (v) for landslide mapping (32% of the papers), and (vi) for monitoring (3% of the papers). Sixty-eight percent of the authors validated the satellite results with ground information or other remote sensing data. Although well-known limitations exist, this bibliographic overview confirms that InSAR is a consolidated tool for many landslide-related applications. [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]

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]

The potential of satellite-based interferometry for landslides activity definition is well known. Many applications have demonstrated that this technique represents a strong supporting tool for landslide risk assessment and monitoring, at both local and regional scale. The ESA' Sentinel-1 (S1) constellation acquires with high revisit-time in a conflict-free operational mode, timely distributing data without costs or restrictions. All these characteristics allow relying upon S1 service for a long-term operational and sustainable use, as a support of both disaster risk reduction and response. For this reason, more and more research projects are based on the use of S1 in geohazards monitoring and early warning. The aim of this work is to present the results achieved in the framework of the European Project (ECHO) U-Geohaz regarding landslides monitoring and early warning supporting tools based on S1. The study area of the project is the Valle d'Aosta region (VDA) that is widely affected by landslide process of different size and typology. Specifically, the Deep-Seated Gravitational Slope Deformations (DSGSDs) are the most representative in terms of area coverage. The study of the state of activity and evolution of these phenomena is very important because DSGSDs affect entire valley flanks and several villages have been built on them or nearby. The use of S1-based interferometry can potentially give a near-real time information on their activity over the whole region supporting decision makers and early warning systems. At the same time, VDA presents challenging characteristics for what concerns the radar response and thus the obtainable results. The main limiting factor is the snow coverage, which is also strongly related to the topography. The topographic relief is highly variable, ranging from 300 m a.s.l. to peaks higher than 4000 m a.s.l. with steep slopes. The regional climate is characterized by wide range of temperatures varying a lot from the mountainous zone to the bottom of the valleys, implying also a strong variation in snow precipitations. This strong variation, in space and time, affects the DInSAR results in terms of coherence and spatial coverage. In this context, a strong effort has been done to develop a processing approach to improve the spatial and temporal sampling, without losing the quality of the results. Moreover, a method that extracts the most significant Active Deformation Areas (ADA) in a semi-automatic way has been adapted and applied. The main results will be exposed. [ABSTRACT FROM AUTHOR]

A relevant change in the use of SAR interferometry for risk management and reduction has been marked by the launch of the S-1 A and S-1 B, in 2014 and 2016 respectively, which ensure a SAR acquisition every 6 days above the entire Earth and make images available few hours after the acquisition without costs and limitations. S-1 represents a reliable and low cost tool for remote monitoring at both local and national-scale, which can potentially be exploited by administrative entities and Civil Protection authorities involved in risk management activities. "U-Geohaz, Geohazard impact assessment for urban areas" is a two-year project, started the 1st of January 2018, co-funded by the European Commission, Directorate-General Humanitarian Aid and Civil Protection (ECHO). The main aim of the project is to develop a methodology based on the SAR images acquired by Sentinel-1 (S-1) constellation to assess continuously the potential impact of geohazards on urban areas and critical infrastructures. Starting from the experience and the results obtained in the previous ECHO project SAFETY (2016-2017), the aim is to make a step forward, from periodically updated maps to a near-real time geohazards mapping and monitoring. U-Geohaz will provide tools to exploit the 6-days repeatability of S1 to support early warning systems for landslide and volcanic geohazards and to evaluate the expected damage. The consortium of U-Geohaz is composed of 18 partners, from 11 European countries, including 12 Geological Surveys and 3 Civil Protection Authorities that will support the implementation of tools to be operationally useful in risk management. The use of all the developed products will be implemented in the activities of the Civil Protection Authorities involved in the project. All the implemented procedure and tools are tested and will be demonstrated on the real test scenarios of Canary Island (Gran Canaria, Tenerife and El Hierro islands, Spain) and Valle d'Aosta (Italy). The main results achieved over the two test-sites and the future steps of the project will be presented and discussed. [ABSTRACT FROM AUTHOR]

The potential use of the integration of PSI (Persistent Scatterer Interferometry) and GB-InSAR (Ground-based Synthetic Aperture Radar Interferometry) for landslide hazard mitigation was evaluated for mapping and monitoring activities of the San Fratello landslide (Sicily, Italy). Intense and exceptional rainfall events are the main factors that triggered several slope movements in the study area, which is susceptible to landslides, because of its steep slopes and silty-clayey sedimentary cover. In the last three centuries, the town of San Fratello was affected by three large landslides, developed in different periods: the oldest one occurred in 1754, damaging the northeastern sector of the town; in 1922 a large landslide completely destroyed a wide area in the western hillside of the town. In this paper, the attention is focussed on the most recent landslide that occurred on 14 February 2010: in this case, the phenomenon produced the failure of a large sector of the eastern hillside, causing severe damages to buildings and infrastructures. In particular, several slow-moving rotational and translational slides occurred in the area, making it suitable to monitor ground instability through different InSAR techniques. PS-InSAR(tm) (permanent scatterers SAR interferometry) techniques, using ERS-1/ERS-2, ENVISAT, RADARSAT-1, and COSMO-SkyMed SAR images, were applied to analyze ground displacements during pre- and post-event phases. Moreover, during the post-event phase in March 2010, a GB-InSAR system, able to acquire data continuously every 14 min, was installed collecting ground displacement maps for a period of about three years, until March 2013. Through the integration of space-borne and ground-based data sets, ground deformation velocity maps were obtained, providing a more accurate delimitation of the February 2010 landslide boundary, with respect to the carried out traditional geomorphological field survey. The integration of GB-InSAR and PSI techniques proved to be very effective in landslide mapping in the San Fratello test site, representing a valid scientific support for local authorities and decision makers during the post-emergency management. [ABSTRACT FROM AUTHOR]