Conventionally, contact sensors such as accelerometers are used to conduct vibration-based structural health monitoring (VBSHM), providing accurate measurements but with deployment significantly limited by installation and maintenance challenges. Remote sensing alternatives for VBSHM have consequently garnered interest for alleviating monitoring costs. Several techniques have been developed previously: uncrewed aerial vehicles (UAVs) equipped with cameras for digital image correlation, and both ground-based lidar and millimetre-wave Doppler radar in either real or synthetic aperture modes – however these all require onsite proximity, limiting their coverage. Spaceborne sensing offers a less occluded vantage point from an orbiting platform, both features vastly improving sensor coverage. Synthetic aperture radar (SAR) is a widely used technology, where in an SHM context interferometric SAR (InSAR) has been noted for utility in measuring the long-term displacement of structural elements. As InSAR functions by comparing multiple SAR acquisitions of an area, its sampling rate – dictated by the revisit time of EO missions – is too low for VBSHM purposes. The alternative presented here is micro-Doppler SAR (MDSAR), which measures motion using a single SAR image and can achieve the sampling rates required, providing a complement to conventional SHM approaches. MDSAR functions by estimating the Doppler shift caused by a vibrating target, which is observed in a SAR signal. These shifts can be related to a target velocity along the line of sight, and sampled at rates matching the oscillation frequencies of large structures.

This paper presents an MDSAR technique, showing time history and spectral results both of calibration tests and a validation experiment conducted on a bridge. The input data are high-resolution, single-pass SAR images of real-world targets obtained through commercial SAR companies, with synchronous ground truth measurements gathered by conventional sensing. Calibration measurements of radar targets showed good agreement between time histories for velocities down to RMS 0.66 mm/s for 2 Hz oscillation with a 0.4 Hz amplitude modulation similar to that observed for bridges, with RMSE values of 64%, and a spectral residual value less than the frequency resolution of 0.07 Hz.

Validation experiments were carried out on the South Portland Street Suspension Bridge in Glasgow, UK, with ground-truth from an installed accelerometer monitoring system. They are consistent with calibration tests and demonstrate the feasibility of measuring vibrational velocities as low as 1 mm/s with MDSAR. In the time domain, the average measurement error is approximately 1 mm/s, comparable to the true velocities of the bridge. In the frequency domain, the technique performs well in identifying the dominant vibrational frequency, with a residual less than the frequency resolution of 0.06 Hz determined by the SAR acquisition duration of 16 s. Full modal identification (of mode shape components) is currently limited by the characteristics of current SAR missions, including radar wavelength, signal-to-noise ratio, and acquisition time. In the absence of modal coupling, partial information e.g. modeshape phase components, is retrievable. Although MDSAR cannot yet supplant onsite SHM methods, it can still provide valuable insights which could integrate into hybrid systems and scope remains for refinement of measurements.

Structural health monitoring (SHM) of aging bridges requires reliable methods to capture deformation behavior at multiple scales. Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) provides millimeter-level displacement measurements, but interpretation of these datasets remains challenging for slender structures.
This study presents an anomaly detection framework for PS-InSAR displacement data combining temporal feature analysis and spatial structuring. Features such as velocity and thermal sensitivity are analyzed using an unsupervised Isolation Forest model, with SHapley Additive exPlanations (SHAP) used for interpretability. Persistent scatterers are projected onto the bridge axis and aggregated into span-scale zones, and a normalized relative anomaly density metric is introduced to enable cross-satellite comparison.
The framework is applied to descending-pass Sentinel-1 and RADARSAT Constellation Mission datasets over the Victoria Bridge in Montreal. Results show consistent identification of key anomalous segments across datasets despite differences in spatial resolution.
The proposed approach provides a structured and interpretable framework for PS-InSAR-based bridge monitoring.

Monitoring suspension bridges subjected to environmental and operational loads using satellite-based methods is challenging due to the complexity of these structures. The current study investigated the satellite-based Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) displacements measured for the Lower Liard River (LLR) Suspension Bridge, located on the Alaska Highway in northern British Columbia, Canada, and compared them with the displacements obtained from the LLR Bridge finite element structural. The PS-InSAR analysis was performed using C-band RADARSAT Constellation Mission (RCM) data acquired during the ice-off season of 2025 and the line-of-sight (LOS) thermal displacements along the bridge deck were determined for temperatures within the range of +30°C and -45°C. InSAR vertical displacement obtained through a LOS decomposition, was found to be in good agreement with the FEM results, especially for positive temperatures.

Remote sensing techniques, particularly Interferometric Synthetic Aperture Radar (InSAR), offer a promising, cost-effective solution for civil infrastructure monitoring without the need for on-site instrumentation. Among InSAR methods, Persistent Scatterer Interferometry (PSI) exploits temporally stable scatterers to measure ground displacements with millimetric accuracy.

However, the PSI technique faces inherent limitations when applied to complex structural systems such as long-span bridges. In these cases, the deformation may differ from the simple, linear models typically assumed for ground motion, leading to loss of phase coherence and phase ambiguity issues. Consequently, potentially valuable – but low-coherence – scatterers are often discarded from analysis, resulting in an incomplete interpretation of the structure behaviour.

This work introduces a novel framework to integrate physics-based structural models (e.g. finite element models) with PSI to overcome these limitations. Rather than focusing on individual pixels, the model accounts for spatial correlation of the persistent scatterers using the structural model of the bridge. The method enables the inclusion of low-coherence Persistent Scatterers that would otherwise be excluded, enhancing the spatial density and reliability of displacement data. The methodology is applied to the Colle Isarco Viaduct (Vipiteno, Italy), a reinforced concrete bridge monitored with multi-temporal COSMO-SkyMed X-band SAR data. The infrastructure is also monitored with topographic survey measurements, which are used in this work as a validation benchmark to assess the accuracy of the results.

Results demonstrate that the proposed framework successfully reduces uncertainty in LOS displacement for poorly coherent PSs from approximately 8 mm to 3 mm, within the uncertainty bounds of the benchmark. Furthermore, the enhanced interpretation of low-coherence points provides valuable insights into the bridge structural response and thermal deformation patterns.

Satellite-based remote sensing tools such as Synthetic Aperture Radar (SAR) Interferometry (InSAR) has emerged as a potential tool for condition monitoring of railway track and infrastructure. This is due to its frequent and stable collection of data without requiring personnel or capacity occupation on the railway track.

SAR is an active radar, meaning that it can collect images during cloud coverage and do not rely on sunlight. It collects scattered reflections as complex images with pixel intensity and phase. Current satellites instrumented with SAR have a passing frequency over a location on the earth at best 6 days. Interferometry exploits the phase difference between two or more SAR images collected at either different positions or times, which effectively can give information about the relative difference in distance between the images. Differential InSAR (D-InSAR) considers SAR images of the same location at different times, resulting in measurements of ground motion in the satellite line of sight. The system design of the radar used for SAR has implications on the spatial resolution of the earth surface measurement, which is generally inversely proportional to spatial coverage. The aim of this paper is to assess the applicability of Sentinel-1 and TerraSAR-X data for track irregularity monitoring considering their different system design of the radar. Sentinel-1 has wider coverage and lower resolution compared to TerraSAR-X. In contrast, Sentinel-1 satellite data is open to global users. Exploring its possibilities and limitations for railway maintenance supports the development of more robust and cost-efficient maintenance decisions.

The case study for this assessment is a transition zone between railway bridge and ballasted track in Sweden. Transition zones are interesting objects of study from a condition monitoring point of view as they often exhibit differential settlements and therefore worse track geometry. This is because of differences in settlement resistance for the different types of track structure that meet in the transition zone. The reference geometry data for the transition zone consists of measured track irregularities from chord-based track monitoring vehicles which are used to assess railway longitudinal levels (vertical track irregularities) at three different wavelength ranges, D1 = 3-25 m, D2 = 25-70m, and D3 = 70-150m. Shorter wavelength longitudinal level variations is associated with safety levels and is the basis for track maintenance in Sweden, whereas the longer wavelengths are associated with ride comfort.

The 6 February 2023 Türkiye-Syria earthquake sequence (Mw 7.8) highlighted the need for continuous, high-precision geodetic monitoring across the convergence zone of the African, Arabian, Eurasian and Anatolian plates. In this setting, interseismic deformation evolves slowly, while transient changes may occur over weeks to months. The objective of this work is to demonstrate a single cross-border deployment that produces time-synchronised displacement time series suitable for joint interpretation and hazard-oriented research.

This contribution presents the Asia Minor GNSS Monitoring Network, a cross-border array of autonomous low-cost GNSS stations delivering daily absolute displacement solutions using Precise Point Positioning (PPP), enabling coherent comparison of sites separated by thousands of kilometres. Each station processes multi-constellation observations (> 40 satellites) and applies automated corrections for satellite clocks, orbits, and tropospheric and ionospheric delays, producing stable daily X, Y, Z millimetre-level solutions that are transmitted into the network for time-synchronised evaluation.

It currently includes stations on three major tectonic plates: the Anatolian Plate (Adana, Türkiye, since 2023), the Arabian Plate (Amman, Jordan, since 2025), and the Eurasian Plate (Stade, Hamburg and GFZ Potsdam, Germany; Geosphere Austria – Conrad Observatory, Vienna, Austria; Cerema, Bordeaux, France; Breda, Netherlands).

Daily solutions are ingested into a central time-synchronised displacement database to enable consistent comparison across sites and time.

A key methodological step is the calibration of compact low-cost GNSS instrumentation to achieve geodetic-grade repeatability over long durations.

Parallel operation since 2021 with the GFZ IGS reference station in Potsdam confirms millimetre-level daily position stability. Independent reference solutions in cooperation with Cerema (Bordeaux, France since 2023) and Geosphere Austria at the Conrad Observatory (2025) further validate the network. The network functions as an open scientific infrastructure, with daily displacement results accessible to participating institutions for geodynamic research and seismic hazard assessment.

For May to October 2025, monthly three-dimensional displacement magnitudes at the Asia Minor stations range between 5 and 23 mm. A preliminary comparison with regional earthquake occurrence (Mw > 4) shows that months with higher cumulative displacement co-occur with higher reported seismic activity, whereas months with lower cumulative displacement align with fewer recorded events. This observation is presented as hypothesis-generating and does not imply causality or predictive capability.

Within the scope of the conference, the contribution is a transferable workflow for integrating autonomous PPP outputs into a shared, time-aligned database that supports multi-site deformation analysis and interpretation under operational and environmental variability. The same autonomous PPP workflow is directly transferable to civil infrastructure deformation monitoring under seismic loading.

Ongoing work with the University of Exeter will introduce physics-informed neural networks (PINNs) applied to the Asia Minor PPP time series, embedding deformation physics as constraints to assist interpretation of long-term tectonic signals.