a b s t r a c t Persistent Scatterer Interferometry (PSI) is a powerful remote sensing technique able to measure and monitor displacements of the Earth's surface over time. Specifically, PSI is a radar-based technique that belongs to the group of differential interferometric Synthetic Aperture Radar (SAR). This paper provides a review of such PSI technique. It firstly recalls the basic principles of SAR interferometry, differential SAR interferometry and PSI. Then, a review of the main PSI algorithms proposed in the literature is provided, describing the main approaches and the most important works devoted to single aspects of PSI. A central part of this paper is devoted to the discussion of different characteristics and technical aspects of PSI, e.g. SAR data availability, maximum deformation rates, deformation time series, thermal expansion component of PSI observations, etc. The paper then goes through the most important PSI validation activities, which have provided valuable inputs for the PSI development and its acceptability at scientific, technical and commercial level. This is followed by a description of the main PSI applications developed in the last fifteen years. The paper concludes with a discussion of the main open PSI problems and the associated future research lines.

Despite landslides impact the society worldwide every day, landslide information is inhomogeneous and lacking. When landslides occur in remote areas or where the availability of optical images is rare due to cloud persistence, they might remain unknown, or unnoticed for long time, preventing studies and hampering civil protection operations. The unprecedented availability of SAR C-band images provided by the Sentinel-1 constellation offers the opportunity to propose new solutions to detect landslides events. In this work, we perform a systematic assessment of Sentinel-1 SAR C-band images acquired before and after known events. We present the results of a pilot study on 32 worldwide cases of rapid landslides entailing different types, sizes, slope expositions, as well as pre-existing land cover, triggering factors and climatic regimes. Results show that in about eighty-four percent of the cases, changes caused by landslides on SAR amplitudes are unambiguous, whereas only in about thirteen percent of the cases there is no evidence. On the other hand, the signal does not allow for a systematic use to produce inventories because only in 8 cases, a delineation of the landslide borders (i.e., mapping) can be manually attempted. In a few cases, cascade multi-hazard (e.g., floods caused by landslides) and evidences of extreme triggering factors (e.g., strong earthquakes or very rapid snow melting) were detected. The method promises to increase the availability of information on landslides at different spatial and temporal scales with benefits for event magnitude assessment during weather-related emergencies, model tuning, and landslide forecast model validation, in particular when accurate mapping is not required.

This paper illustrates the potential of Sentinel-1 for landslide detection, Accepted 23 March 2016 mapping and characterization with the aim of updating inventory maps and monitoring landslide activity. The study area is located in Molise, one of the smallest regions of Italy, where landslide processes are frequent. The results achieved by integrating Differential Synthetic Aperture Radar Interferometry (DInSAR) deformation maps and time series, and Geographical Information System (GIS) multilayer analysis (optical, geological, geomorphological, etc.) are shown. The adopted methodology is described followed by an analysis of future perspectives. Sixty-two landslides have been detected, thus allowing the updating of pre-existing landslide inventory maps. The results of our ongoing research show that Sentinel-1 might represent a significant improvement in terms of exploitation of SAR data for landslide mapping and monitoring due to both the shorter revisit time (up to 6 days in the close future) and the wavelength used, which determine an higher coherence compared to other SAR sensors

This paper is focused on the estimation of the thermal expansion of buildings and infrastructures using X-band Persistent Scatterer Interferometry (PSI) observations. For this purpose an extended PSI model is used, which allows separating the thermal expansion from the total observed deformation thus generating a new PSI product: the map of the thermal expansion parameter, named thermal map. The core of the paper is devoted to the exploitation of the information contained in the thermal maps: three examples are discussed in detail, which concern a viaduct, a set of industrial buildings and two skyscrapers. The thermal maps can be used to derive the thermal expansion coefficient of the observed objects and information on their static structure. In addition, the paper illustrates the distortions in the PSI deformation products that occur if the thermal expansion is not explicitly modelled. Finally, an inter-comparison exercise is described, where the thermal expansion coefficients estimated by PSI are compared with those derived by a Ku-band ground-based SAR campaign.

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.

No abstract

No abstract

Landslides in reservoir contexts are a well-recognised hazard that may lead to dangerous situations regarding infrastructures and people’s safety. Satellite-based radar interferometry is proving to be a reliable method to monitor the activity of landslides in such contexts. Here, we present a DInSAR (Differential Interferometric Synthetic Aperture Radar) analysis of Sentinel-1 images that exemplifies the usefulness of the technique to recognize and monitor landslides in the Rules Reservoir (Southern Spain). The integration of DInSAR results with a comprehensive geomorphological study allowed us to understand the typology, evolution and triggering factors of three active landslides: Lorenzo-1, Rules Viaduct and El Arrecife. We could distinguish between rotational and translational landslides and, thus, we evaluated the potential hazards related to these typologies, i.e., retrogression (Lorenzo-1 and Rules Viaduct landslides) or catastrophic slope failure (El Arrecife Landslide), respectively. We also observed how changes in the water level of the reservoir influence the landslide’s behaviour. Additionally, we were able to monitor the stability of the Rules Dam as well as detect the deformation of a highway viaduct that crosses a branch of the reservoir. Overall, we consider that other techniques must be applied to continue monitoring the movements, especially in the El Arrecife Landslide, in order to avoid future structural damages and fatalities.