This work concerns a proposal of the integration of InSAR (Interferometric Synthetic Aperture Radar) data acquired by ground-based (GB) and satellite platforms. The selected test site is the Åknes rockslide, which affects the western Norwegian coast. The availability of GB-InSAR and satellite InSAR data and the accessibility of a wide literature make the landslide suitable for testing the proposed procedure. The first step consists of the organization of a geodatabase, performed in the GIS environment, containing all of the available data. The second step concerns the analysis of satellite and GB-InSAR data, separately. Two datasets, acquired by RADARSAT-2 (related to a period between October 2008 and August 2013) and by a combination of TerraSAR-X and TanDEM-X (acquired between July 2010 and October 2012), both of them in ascending orbit, processed applying SBAS (Small BAseline Subset) method, are available. GB-InSAR data related to five different campaigns of measurements, referred to the summer seasons of 2006, 2008, 2009, 2010 and 2012, are available, as well. The third step relies on data integration, performed firstly from a qualitative point of view and later from a semi-quantitative point of view. The results of the proposed procedure have been validated by comparing them to GPS (Global Positioning System) data. The proposed procedure allowed us to better define landslide sectors in terms of different ranges of displacements. From a qualitative point of view, stable and unstable areas have been distinguished. In the sector concerning movement, two different sectors have been defined thanks to the results of the semi-quantitative integration step: the first sector, concerning displacement values higher than 10 mm, and the 2nd sector, where the displacements did not exceed a 10-mm value of displacement in the analyzed period.

Landslides are common phenomena that occur worldwide and are a main cause of loss of life and damage to property. The hazards associated with landslides are a challenging concern in many countries, including Italy. Over the last 15 years, an increasing number of applications have aimed to demonstrate the applicability of images captured by space-borne Synthetic Aperture Radar (SAR) sensors in slope instability investigations. InSAR (SAR interferometry) is currently one of the most exploited techniques for the assessment of ground displacements, and it is becoming a consolidated tool for Civil Protection institutions in addressing landslide risk. This paper presents a subset of the results obtained in Italy within the framework of SAR-based programmes and applications intended to test the potential application of C- and X-band satellite interferometry during different Civil Protection activities (namely prevention, prevision, emergency response and post-emergency phases) performed to manage landslide risk. Analysis of satellite SAR data is demonstrated to play a major role in the investigation of landslide-related events at different stages, including detection, mapping, monitoring, characterization and prediction. In addition, this paper also discusses the limitations that still exist and must be overcome in the coming years to manage the transition of satellite SAR systems towards complete operational use in landslide risk management practices.

This paper presents the main results of the GB-InSAR (ground based interferometric synthetic aperture radar) monitoring of the Capriglio landslide (Northern Apennines, Emilia Romagna Region, Italy), activated on 6 April 2013. The landslide, triggered by prolonged rainfall, is constituted by two main adjacent enlarging bodies with a roto-translational kinematics. They activated in sequence and subsequently joined into a large earth flow, channelizing downstream of the Bardea Creek, for a total length of about 3600 m. The displacement rate of this combined mass was quite high, so that the landslide toe evolved with velocities of several tens of meters per day (with peaks of 70–80 m/day) in the first month, and of several meters per day (with peaks of 13–14 m/day) from early May to mid-July 2013. In the crown area, the landslide completely destroyed a 450 m sector of provincial roadway S.P. 101, and its retrogression tendency exposed the villages of Capriglio and Pianestolla, located in the upper watershed area of the Bardea Creek, to great danger. Furthermore, the advancing toe seriously threatened the Antria bridge, representing the “Massese” provincial roadway S.P. 665R transect over the Bardea Creek, the only strategic roadway left able to connect the above-mentioned villages. With the final aim of supporting local authorities in the hazard assessment and risk management during the emergency phase, on 4 May 2013 aerial optical surveys were conducted to accurately map the landslide extension and evolution. Moreover, a GB-InSAR monitoring campaign was started in order to assess displacements of the whole landslide area. The versatility and flexibility of the GB-InSAR sensors allowed acquiring data with two different configurations, designed and set up to continuously retrieve information on the landslide movement rates (both in its upper slow-moving sectors and in its fast-moving toe). The first acquisition mode revealed that the Capriglio and Pianestolla villages were affected by minor displacements (at an order of magnitude of a few millimeters per month). The second acquisition mode allowed to acquire data every 28 seconds, reaching very high temporal resolution values by applying the GB-InSAR technique.

Information regarding the shape and depth of a landslide sliding surface (LSS) is fundamental for the estimation of the volume of the unstable masses, which in turn is of primary importance for the assessment of landslide magnitude and risk scenarios as well as in refining stability analyses. To assess an LSS is not an easy task and is generally time-consuming and expensive. In this work, a method existing in the literature, based on the inclination of movement vectors along a cross-section to estimate the depth and geometry LSSs, is used for the first time while exploiting satellite interferometric data. Given the advent of satellite interferometric data and the related increasing availability of spatially dense and accurate measurements, we test the effectiveness of this method—here named the vector inclination method (VIM)—to four case landslides located in Italy characterized by different types of movement, kinematics and volume. Geotechnical and geophysical information of the LSS is used to validate the method. Our results show that each of the presented cases provides useful insight into the validity of VIM using satellite interferometric data. The main advantages of VIM applied to satellite interferometry are that it enables estimation of the LSS with a theoretical worldwide coverage, as well as with no need for onsite instrumentation or even direct access; however, a good density of measurement points in both ascending and descending geometry is necessary. The combined use of VIM and traditional investigations can provide a more accurate LSS model.

Slope failures are life-threatening geohazards well-known in the mining industry, where a single accident can endanger workers and cause million dollars’ -worth of activity downtime. Therefore, a detailed ground deformation map of an open-pit mine represents a vital planning tool and high-frequency monitoring is pivotal, since false or anticipated alarms may represent a higher impact than missed alarms. This article presents an application of interferometric satellite data from Sentinel-1. The scope of the study is showing the potential of the new generation of satellites for the detection of the boundary, typology, and kinematics of the on-going slope instabilities in open-pit mines. Most notably, this experience discloses how the short revisiting time (six days) permits the implementation of time of failure forecasting methods, which so far were a prerogative of ground-based monitoring systems. Only recently, a few experiences have shown the possibility of (a posteriori) predicting slope failures using displacement time series measured from satellite; the case study here described represents one of such first examples. Moreover, 11 other areas of instability have been detected and classified in terms of subsidence (sediment compaction) or slope failures, based on considerations concerning the acquisition geometry used to detect the movements. The movement vectors along the ascending and descending lines of sight have been combined to compute horizontal and vertical vectors, which have been employed to infer the geometry of the sliding surface of some selected slope instabilities. Despite the advancements of the technique, clear limitations still exist and are discussed in this article.