InSAR capabilities allow us to understand ground deformations in large metropolitan areas, this is key to assessing site conditions in areas in an inherently expanding context. The multi-temporal interferometry of SAR data records ground surface displacement velocities over large metropolitan areas, identifying anomalous and potential geological hazards. The metropolitan city of Concepción, Chile, is an alluvial basin in one of the world’s most seismically active subduction zones, where many subduction earthquakes have occurred throughout history. In this study, we monitored the deformations of the ground surface in the metropolitan area of Concepción using two interferometric techniques, the first being Persistent Scatterer Interferometry (PSI) and the second, the Small Baseline Subset (SBAS) technique. To do this, we have used the same Sentinel-1 dataset, obtaining ground movement rates between 2019 and 2021. The velocities were aligned with the GNSS station available in the area. Ground deformation patterns show local deformations depending on factors such as soil type and heterogeneity, and regional deformations due to geographical location in the subduction area. Our results highlight the similarity of the deformation rates obtained with different processing techniques and have also allowed us to identify areas of deformation and compare them to site conditions. These results are essential to evaluate ground conditions and contribute to urban planning and risk management in highly seismic areas.

This study investigates vertical soil movement, a subsidence phenomenon affecting infrastructure and communities in the Emilia-Romagna region (Italy). Building upon previous research—initially based on leveling and GNSS observations and later expanded with interferometric synthetic aperture radar (InSAR)—this study focuses on recent data from 2016 to 2021. A key innovation is the use of dual-geometry ascending and descending acquisitions to derive the vertical and the east–west movement components, a technique not previously applied at a regional scale in this area. The integration of advanced geodetic techniques involved processing 1208 Sentinel-1 satellite images with the SqueeSAR^® algorithm and analyzing data from 28 GNSS permanent stations using the precise point positioning (PPP) methodology. By calibrating the InSAR data with GNSS measurements, we generated a comprehensive subsidence map for the study period, identifying trends and anomalies. The analysis produced 13.5 million measurement points, calibrated and validated using multiple GNSS stations. The final dataset, processed through geostatistical methods, provided a high-resolution (100-m) regional subsidence map covering nearly 11,000 square kilometers. Finally, the vertical soil movement map for 2016–2021 was developed, featuring isokinetic curves with an interval of 2.5 mm/year. The results underscore the value of integrating these geodetic techniques for effective environmental monitoring in subsidence-prone areas. Furthermore, comparisons with previous subsidence maps reveal the evolution of soil movement in Emilia-Romagna, reinforcing the importance of these maps as essential tools for precise subsidence monitoring.

The InSAR technique is known to be a powerful tool for precise monitoring of wide areas in terms of displacements. It is conceivable to also use this technique to monitor landslide areas, but geometrical distortions due to ground morphology and land cover could make InSAR processing ineffective for such applications. Because of the computational burden of InSAR processing, it is important to have preliminary knowledge about the possible suitability of the technique for the inspected area before acquiring and processing the data. This paper aims to perform a preliminary analysis of the InSAR sensitivity for the specific case of landslide monitoring. A new approach is proposed considering aspects specific to landslide displacements, which are basically tangent to the slope direction. Pre-processed coherence maps were used to account for the impact of land cover. The whole analysis can be carried out without acquiring cumbersome SAR datasets and can be used as a preliminary step. The Italian Emilia-Romagna region has been considered as the study area, with landslide areas accounting for more than 12% of its territory. The outcomes show that the inspected area has favourable morphological conditions, mainly thanks to its mild slopes and the limited number of landslides facing north, but the land cover has a strong negative impact on the InSAR sensitivity. Nevertheless, 7.5% of the landslide areas have promising conditions for monitoring using radar interferometry.

In 2011, the IGMI (Istituto Geografico Militare Italiano) defined the new Italian geodetic reference, materialized by the Rete Dinamica Nazionale (RDN), a cluster of 99 GNSS permanent stations located in Italy and, few of them, in neighbouring areas. RDN also includes some IGS and EPN sites, so that it constitutes a densification of those two networks. The official coordinates of the 99 GNSS stations were initially obtained by computing a limited period of 28 days starting from the end of 2007 and aligned to the datum ETRS89-ETRF2000 at epoch 2008.0. After years of continuously acquired data, other studies published the stations’ coordinates together with the associated velocities. This paper presents the updated results of the velocity trends considering the whole dataset now available, consisting of 15 years of data. The analysis considered only the 77 stations that worked consistently for at least five years. The workflow starts with the archive organization and pre-analysis, followed by the geodetic computation using the Precise Point Positioning approach implemented in the GIPSYX software. After the post-processing of the solutions, which included the alignment to the ETRF2000 frame and the analysis of discontinuities, the mean velocities have been computed. The latter were compared to those estimated in a previous work basing on 8 years long dataset. The comparison shows the overall agreement between the linear trends, but also highlights the importance of considering the whole dataset nowadays available to assess the behaviour of those few sites who underwent velocity changes over time.

Synthetic Aperture Radar Interferometry (InSAR) is widely used to monitor ground deformation, but its results are relative to a local satellite-based reference system. To enable consistent geodetic interpretation, InSAR velocities must be aligned to a terrestrial reference frame, typically using Global Navigation Satellite System (GNSS) data. This study aims to identify the most effective referencing strategy to align ascending and descending InSAR datasets to the European Terrestrial Reference Frame (ETRF), using a dense GNSS network in a subsidence-affected area of northern Italy. We tested several referencing approaches by varying: (i) the number and configuration of GNSS stations, (ii) the density of Persistent Scatterers (PS) used to calculate local InSAR velocities, and (iii) the modeling of InSAR-GNSS differences, using either a bias, a plane, or a second-order polynomial surface. Results show that the optimal referencing is achieved by modeling the differences with a planar surface, using all available GNSS stations, and computing InSAR velocities from PS within 100 m of each station. This approach minimized post-referencing residuals more effectively than other methods, including polynomial fitting. Following referencing, InSAR data from both geometries are merged to extract the vertical (Up) and horizontal (East) components of motion, demonstrating alignment with the GNSS-based reference system. These findings highlight how referencing performance depends on both the modeling strategy and GNSS-PS configuration, providing guidance for improving InSAR accuracy in geodetic applications.