Land subsidence affects many areas of the world, posing a serious threat to human structures and infrastructures. It can be effectively monitored using ground-based and remote sensing techniques, such as the Global Navigation Satellite System (GNSS) and Interferometric Synthetic Aperture Radar (InSAR). GNSS provides high precision measurements, but in a limited number of points, and is time-consuming, while InSAR allows one to obtain a very large number of measurement points, but only in areas characterized by a high and constant reflectivity of the signal. The aim of this work is to propose an approach to combine the two techniques, overcoming the limits of each of them. The approach was applied in the Po River Delta (PRD), an area located in Northern Italy and historically affected by land subsidence. Ground-based GNSS data from three continuous stations (CGNSS) and 46 non-permanent sites (NPS) measured in 2016, 2018, and 2020, and Sentinel-1 and COSMO-SkyMed SAR data acquired from 2016 to 2020, were considered. In the first phase of the method, InSAR processing was calibrated and verified through CGNSS measurements; subsequently, the calibrated interferometric data were used to validate the GNSS measurements of the NPS. In the second phase, the datasets were integrated to provide an efficient monitoring system, extracting high-resolution deformation maps. The results showed a good agreement between the different sources of data, a high correlation between the displacement rate and the age of the emerged surfaces composed of unconsolidated fine sediments, and high land subsidence rates along the coastal area (up to 16–18 mm/year), where the most recent deposits outcrop. The proposed approach makes it possible to overcome the disadvantages of each technique by providing more complete and detailed information for a better understanding of the ongoing phenomenon.

River deltas are very complex environments vulnerable to flooding. Most of the world’s deltas are facing the immediate threat of land subsidence that jeopardizes the safety of millions of people worldwide. In Italy, the Po River Delta (PRD) (Northeast Italy) is an area historically affected by high rate of subsidence due to natural and anthropic factors. Even if the subsidence rates remarkably reduced during the last three decades, this process continues to be alarming in particular in low-lying sectors and along the coastline, where the loss of elevation, combined with the sea-level rise, increases the risk related to flooding. In this study, we monitored the subsidence affecting the entire PRD area with advanced differential interferometric synthetic aperture radar (A-DInSAR) techniques applied to three C-band SAR data sets acquired by the European Remote Sensing satellites, Environmental Satellite, and Sentinel-1A satellite in the last 25 years (from 1992 to 2017). The results of the interferometric processing, consisting of both mean velocity and displacement time series along the satellite line of sight, validated by comparison with levelling and global positioning system measurements, show increasing subsidence moving from the inland to the coastline, with maximum deformation velocities, for the most recent data, in the order of −30 mm year⁻¹. In particular, many embankments near the coastal area are affected by high values of subsidence, which increase the flooding hazard of the entire deltaic territory. This work shows the importance of adopting A-DInSAR techniques to update the knowledge of the extent and rates of deformation of subsiding areas in low-lying territories such as river deltas. The outputs of such monitoring can be of primary importance for the future protection of the territory and the flooding risk mitigation.

The Po River Delta (PRD, Northern Italy) has been historically affected by land subsidence due to natural processes and human activities, with strong impacts on the stability of the natural ecosystems and significant socio-economic consequences. This paper is aimed to highlight the spatial and temporal evolution of the land subsidence in the PRD area analyzing the geodetic observations acquired in the last decade. The analysis performed using a moving window approach on Continuous Global Navigation Satellite System (CGNSS) time-series indicates that the velocities, in the order of 6 mm/year, are not affected by significant changes in the analyzed period. Furthermore, the use of non-permanent sites belonging to a new GNSS network (measured in 2016 and 2018) integrated with InSAR data (from 2014 to 2017) allowed us to improve the spatial coverage of data points in the PRD area. The results suggest that the land subsidence velocities in the easternmost part of the area of interest are characterized by values greater than the ones located in the western sectors. In particular, the sites located on the sandy beach ridge in the western sector of the study area are characterized by values greater than −5 mm/year, while rates of about −10 mm/year or lower have been observed at the eastern sites located in the Po river mouths. The morphological analysis indicates that the land subsidence observed in the PRD area is mainly due to the compaction of the shallow layers characterized by organic-rich clay and fresh-water peat.

The structural analysis of degraded historical buildings requires an adequate 3D model of the object. Structure from motion (SfM) photogrammetry and laser scanning geomatics techniques can satisfy this request by providing geometrically affordable data. The accuracy and resolution depend on the instruments and procedures used to extract the 3D models. This work focused on a 3D survey of Illasi Castle, a strongly degraded historical building located in northern Italy, aimed at structural analysis in the prevision of a static recovery. A low-cost drone, a single-lens reflex (SLR) camera, and a smartphone were used in the survey. From each acquired dataset, using the integration between the images acquired by the drone and the SLR camera, a 3D model of the building was extracted by means of the SfM technique. The data were compared with high-precision and high-resolution terrestrial laser scanning (TLS) acquisitions to evaluate the accuracy and performance of the fast and low-cost SfM approach. The results showed a standard deviation value for the point cloud comparisons in the order of 2–3 cm for the best solution (integrating drone and SLR images) and 4–7 cm using smartphone images. Finally, the integration of the best SfM model of the external walls and the TLS model of the internal portion of the building was used in finite element (FE) analysis to provide a safety assessment of the structure.

Results of recent monitoring activities on potentially unstable areas of the NW volcano flank of La Fossa cone (Vulcano Island, Italy) are shown here. They are obtained by integration of data by aerial photogrammetry, terrestrial laser scanning (TLS) and GPS taken in the 1996–2011 time span. A comparison between multi-temporal models built from remote sensing data (photogrammetry and TLS) highlights areas characterized by ~7–10 cm/y positive differences (i.e., elevation increase) in the upper crown of the slope. The GPS measurements confirm these results. Areas characterized by negative differences, related to both mass collapses or small surface lowering, also exist. The higher differences, positive and negative, are always observed in zones affected by higher fumarolic activity. In the 2010–2012 time span, ground motions in the northern part of the crater rim, immediately above the upper part of observed area, are also observed. The results show different trends for both vertical and horizontal displacements of points distributed along the rim, with a magnitude of some centimeters, thus revealing a complex kinematics. A slope stability analysis shows that the safety factors estimated from these data do not indicate evidence of possible imminent failures. Nevertheless, new time series are needed to detect possible changes with the time of the stability conditions, and the monitoring has to go on.

Mass movements represent a serious threat to the stability of human structures and infrastructures, and cause loss of lives and severe damages to human properties every year worldwide. Built structures located on potentially unstable slopes are susceptible to deformations due to the displacement of the ground that at worst can lead to total destruction. Synthetic aperture radar (SAR) data acquired by Sentinel-1 satellites and processed by multi-temporal interferometric SAR (MT-InSAR) techniques can measure centimeter to millimeter-level displacement with weekly to monthly updates, characterizing long-term large-scale behavior of the buildings and slopes. However, the spatial resolution and short wavelength weaken the performance of Sentinel-1 in recognizing features (i.e., single buildings) inside image pixels and maintaining the coherence in mountainous vegetated areas. We have proposed and applied a methodology that combines Sentinel-1 interferometry with ground-based geomatics techniques, i.e., global navigation satellite system (GNSS), terrestrial laser scanning (TLS) and terrestrial structure from motion photogrammetry (SfM), for fully assessing building deformations on a slope located in the north-eastern Italian pre-Alps. GNSS allows verifying the ground deformation estimated by MT-InSAR and provides a reference system for the TLS and SfM measurements, while TLS and SfM allow the behavior of buildings located in the investigated slope to be monitored in great detail. The obtained results show that damaged buildings are located in the most unstable sectors of the slope, but there is no direct relationship between the rate of ground deformation of these sectors and the temporal evolution of damages to a single building, indicating that mass movements cause the displacement of blocks of buildings and each of them reacts differently according to its structural properties. This work shows the capability of MT-InSAR, GNSS, TLS and SfM in monitoring both buildings and geological processes that affect their stability, which plays a key role in geohazard analysis and assessment.