In recent years, the measurement of dam displacements has benefited from a great improvement of existing technology, which has allowed a higher degree of automation. This has led to data collection with an improved temporal and spatial resolution. Robotic total stations and GNSS (Global Navigation Satellite System) techniques, often in an integrated manner, may provide efficient solutions for measuring 3D displacements on precise locations on the outer surfaces of dams. On the other hand, remote-sensing techniques, such as terrestrial laser scanning, ground-based SAR (synthetic aperture radar) and satellite differential interferometric SAR offer the chance to extend the observed region to a large portion of a structure and its surrounding areas, integrating the information that is usually provided in a limited number of in-situ control points. The design and implementation of integrated monitoring systems have been revealed as a strategic solution to analyze different situations in a spatial and temporal context. Research devoted to the optimization of data processing tools has evolved with the aim of improving the accuracy and reliability of the measured deformations. The analysis of the observed data for the interpretation and prediction of dam deformations under external loads has been largely investigated on the basis of purely statistical or deterministic methods. The latter may integrate observation from geodetic, remote-sensing and geotechnical/structural sensors with mechanical models of the dam structure. In this paper, a review of the available technologies for dam deformation monitoring is provided, including those sensors that are already applied in routinary operations and some experimental solutions. The aim was to support people who are working in this field to have a complete view of existing solutions, as well as to understand future directions and trends.

The remote sensing technique known as Differential Synthetic Aperture Radar (SAR) Interferometry (DInSAR) allows the detection and monitoring of ground settlements, by generating deformation velocity maps and displacement time-series having centimeter to millimeter accuracy. These measurements can contribute to the evaluation of the structural conditions of the constructions. Given the settlements, different approaches exist for the assessment of the structural damage, ranging from empirical estimates to detailed finite element calculations. In this work, we integrate the results of a DInSAR analysis with an intermediate semi-empirical model to investigate three buildings located in the southern part of the city of Rome. The model, originally proposed by Finno et al. [(2005). ASCEJournal of Geotechnical and Geoenvironmental Engineering, 131(10), 1199–1210], considers each building as an equivalent laminated beam, where the layers represent the floors and the core material reproduces the infill walls. The results obtained by the model have been compared to the damages observed on the buildings, showing a good agreement and demonstrating that the proposed approach represents an effective and, at the same time, simple assessment tool for rapidly evaluating the conditions of several structures.

We extend the small baseline subset (SBAS) differential synthetic aperture radar (SAR) interferometry (DInSAR) approach to allow the generation of deformation time-series by processing, at the full spatial resolution scale, long sequences of European Remote Sensing (ERS-1 and ERS-2) and Environmental Satellite (ENVISAT) SAR data acquired with the same illumination geometry. In particular, we avoid the generation of ERS/ENVISAT cross-interferograms, which are severely affected by noise phenomena due to the carrier frequency separation of the two SAR systems, and we focus on single-platform interferograms only (i.e. ERS/ERS and ENVISAT/ENVISAT interferograms) that are properly combined by applying the singular value decomposition (SVD)-based SBAS approach. Moreover, we exploit the Doppler centroid variations of the post-2000 acquisitions of the ERS-2 sensor and the carrier frequency difference between the ERS-1/2 and the ENVISAT systems, in order to maximize the number of investigated SAR pixels and to improve their geocoding. The presented results, achieved on two data sets relevant to the Napoli Bay area and to the Murge region, both located in southern Italy, confirm the effectiveness of the extended SBAS technique and demonstrate the relevance of deformation analysis carried out at the scale of single buildings or human-made structures with more than 15 years of ERS and ENVISAT acquisitions.

We have exploited the capability of the differential synthetic aperture radar (SAR) interferometry (DInSAR) technique, referred to as Small BAseline Subset (SBAS) approach, to analyse surface deformation at two distinct spatial scales: a low resolution, large scale, and a fine resolution, local scale. At the large scale, the technique investigates DInSAR data with a ground resolution of the order of 100 m×100 m and leads to generate mean deformation velocity maps and associated time series for areas extending to some thousands of square kilometres. At the local scale, the technique exploits the SAR images at full spatial resolution (typically of the order of 5 m×20 m), detecting and analysing localized deformation phenomena. The study is focused on the city of Rome, Italy, and we used the ERS‐1/2 satellite radar data relevant to the 1995–2000 time period. The presented results demonstrate the capability of the SBAS approach to retrieve, from the low‐resolution DInSAR data, large‐scale deformation information leading to identify several sites affected by significant displacements. Our analysis permitted us to conclude that a major contribution to the detected displacements is due to the consolidation of the alluvial soils present in the area, mostly enforced by the buildings' overload. Furthermore, in a selected area, a detailed analysis was carried out by exploiting the full resolution DInSAR data. In this case we investigated deformation phenomena at the scale of single buildings. As key result we showed that differential displacements of few mm a⁻¹, affecting single man‐made structures or building complexes, could be detected, thus allowing to identify sites that may potentially be involved in critical situations.