Jul 2026· The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences· 0 citations· 21 references
Abstract
Abstract. Aging bridge infrastructure requires efficient, network-scale monitoring, especially in remote areas where traditional in-situ sensors are costly and logistically challenging. This paper presents a remote sensing framework for structural health monitoring based on spaceborne Synthetic Aperture Radar (SAR). The approach combines Persistent Scatterer Interferometry (PSI) and Least Squares Collocation (LSC), implemented through the PHASE open-source MATLAB software, to derive a millimeter-level spatio-temporal displacement model. The methodology is applied to a reinforced-concrete viaduct in the Alpine foothills of Lombardy, Italy, using five years of Copernicus Sentinel-1 data. A custom elevation-based spatial filtering strategy enables the isolation of structural displacements from the surrounding topography. The resulting spatio-temporal displacement model captures the expected seasonal thermal behavior of the structure and highlights localized deviations from the dominant cyclic response. Finally, the SAR-derived model is integrated with UAV photogrammetry and official inspection reports within the P.O.N.T.I. 3D viewer. This multi-source, Digital Twin-like environment facilitates the joint interpretation of remote sensing observations and in-situ evidence, providing a scalable framework to support infrastructure monitoring and management.
Abstract. Monitoring linear infrastructures such as railways and highways with Multitemporal Interferometric Synthetic Aperture Radar (MTInSAR) requires to identify spatial displacement gradients to assess related hazards. Estimating the spatial gradients involves the retrieval of the displacement time series in MTInSAR for coherent pixels. However, the algorithms are computationally expensive because pixels outside the linear infrastructure are processed as they are required to aid the phase unwrapping and atmospheric phase filtering at the linear infrastructure. We propose a new approach which makes use of the known location of the linear infrastructure in the SAR images and estimate the differential displacement velocities along the infrastructure from the wrapped interferometric phases. In this way, the effect of incoherent pixels from outside the linear infrastructure and the potential error propagation during spatial phase unwrapping are mitigated. Our experiments based on TerraSAR-X and Sentinel-1 images show good agreement between the estimated spatial gradient velocities from our method and the conventional MTInSAR results. The sensitivity of the choice of grid size is evident in the resultant Root Mean Square Error (RMSE), which is approximately 0.1 cm/year when compared to the conventional MTInSAR results. This is achieved with a grid size larger than 300 m, which smoothed small variations in the differential velocity. Applying our method on Sentinel-1 images enables computationally efficient monitoring of linear infrastructures exploiting the wide area coverage and availability of the SAR images.
A. Piter, M. Haghshenas Haghighi, M. Motagh· ISPRS Annals of the Photogra...· 0 citations
Abstract. Ground deformation caused by excessive groundwater extraction has become a major environmental concern in agricultural regions worldwide. Interferometric Synthetic Aperture Radar (InSAR) enables large-scale monitoring of ground deformation. However, its performance often decreases in low-coherence areas affected by vegetation growth and irrigation. In this study, we conducted a comparative evaluation of three multi-temporal SBAS-InSAR processing frameworks, MintPy, LiCSBAS, and SARvey, to assess their consistency in monitoring ground deformation across Golestan Province, Iran, using Sentinel-1 data acquired between 2014 and 2024. The analysis included deformation velocity fields, cross-sectional profiles, and time-series displacements, which were compared with temperature and precipitation variations. All three frameworks identified a pronounced deformation zone in the Gorgan Plain, with maximum line-of-sight deformation rates up to 13 cm/year. Quantitative comparisons showed strong correlations among the frameworks (r = 0.80 to 0.89), confirming their mutual reliability even under low coherence conditions. The time-series analysis revealed clear seasonal deformation patterns, with summer subsidence and winter uplift closely related to hydroclimatic fluctuations. Overall, this study demonstrates that multi-temporal SBAS-InSAR approaches can provide consistent and physically meaningful deformation estimates in challenging agricultural environments, offering valuable insights for subsidence monitoring and water resource management.
Mingyue Ma, Mahmud Haghshenas Haghighi, Mahdi Motagh· ISPRS Annals of the Photogra...· 0 citations
(English) Investigating building deformation due to differential settlements is a challenging task, particularly over large areas; however, with the advancement of remote sensing techniques, such investigations have now become feasible. The European Ground Motion Service (EGMS), a component of the Copernicus Land Monitoring Service, represents the largest wide-area Interferometric SAR (InSAR) service ever developed that provides a fully open and free-access data availability. In order to exploit the EGMS results, the challenge lies in finding appropriate methodologies and tools to effectively utilize this wealth of information and create easy-to-read and interpretable maps for building damage assessment and urban risk mitigation procedures.
This PhD thesis proposes a methodology and a novel software tool that transform InSAR-based displacement data into comprehensive geospatial maps through a building-scale spatial differential deformation analysis, enabling the identification and classification of urban buildings susceptible to damage due to differential movements. We focus on spatial differential deformation (i.e., the spatial gradient of deformation) for individual buildings, because most of the significant damage to man-made structures/infrastructures is associated with spatial differential deformation. The final output of the proposed methodology is the so-called “Building Differential Deformation Map” (BDD). This methodology is novel because it provides the advantage of enabling wide-area mapping while keeping the building-level details. The procedure requires two input data: InSAR-derived displacement maps, regardless of the data source, as well as a vector map of building footprints.
This research illustrates the use of EGMS Basic products to perform a multi-scale analysis, including the metropolitan area of Barcelona, the Catalonia region, and ultimately the Spanish nationwide BDD map. This latter map identifies 2,958 buildings vulnerable to damage due to differential settlements. Given the large spatial extent of the Spanish BDD map, a web-based platform has been developed to facilitate visualization and enhance the accessibility of relevant information for all users. In a further step, to enhance the analysis, additional data have been considered. The BDD map has been combined with deformation velocity, building age, considered as an indicator of vulnerability, and population data to provide an initial assessment of the potential impact on residents. This integration has led to the development of a so-called “Potential Impact Map,” which identifies areas that need prioritized attention and resources for risk mitigation.
The robustness of the proposed methodology has been evaluated through a dedicated assessment procedure. This assessment has examined the methodology and its results across different acquisition geometries, demonstrating that the spatial deformation gradient is independent of geometry and across varying time spans. Similarly, validation has been conducted through field surveys to assess building damage, focusing on indicators of differential deformation, such as cracks and fractures in walls and around windows.
(Català) La investigació de la deformació dels edificis deguda a assentaments diferencials és una tasca complexa, especialment en àrees extenses; tanmateix, amb l’avanç de les tècniques de teledetecció, aquest tipus d’estudis s’ha tornat actualment viable. L’European Ground Motion Service (EGMS), com a part del Copernicus Land Monitoring Service, representa el major servei d’Interferometria SAR (InSAR) a gran escala desenvolupat fins ara. Gràcies a les seves característiques tècniques i a la disponibilitat oberta i gratuïta dels seus productes, l’EGMS facilita l’accés a mapes de desplaçament. El repte ara rau en desenvolupar metodologies i eines adequades per aprofitar eficaçment aquesta gran quantitat d’informació i generar mapes fàcils d’interpretar, orientats a l’avaluació del dany en edificis i a la mitigació del risc urbà.
Aquesta tesi doctoral aborda aquest repte mitjançant la proposta d’una metodologia i una eina de programari innovadora que transformen les dades de desplaçament derivades d’InSAR en mapes geoespacials complets, a través d’una anàlisi de deformació diferencial espacial a escala d’edifici. Això permet la identificació i classificació d’edificis urbans susceptibles de patir danys a causa de moviments diferencials. En particular, es posa el focus en la deformació diferencial espacial (és a dir, el gradient espacial de deformació) a nivell individual d’edifici, ja que la majoria dels danys significatius en estructures i infraestructures estan associats a gradients espacials de deformació. El resultat final de la metodologia proposada és l’anomenat “Mapa de Deformació Diferencial d’Edificis” (BDD). Aquesta metodologia és innovadora perquè, a diferència d’estudis previs centrats principalment en àrees reduïdes, permet la cartografia sobre àrees extenses mantenint una anàlisi detallada a nivell d’edifici. La metodologia requereix únicament dos tipus de dades d’entrada: mapes de desplaçament derivats d’InSAR, independentment de la font de dades, i un mapa vectorial de la petjada dels edificis.
Aquest treball il·lustra l’ús dels productes bàsics de l’EGMS per realitzar una anàlisi multiescala, incloent l’àrea metropolitana de Barcelona, la regió de Catalunya i, finalment, el mapa BDD de tota Espanya. Aquest mapa inclou 2.958 edificis vulnerables a patir danys a causa d’assentaments diferencials. Donada la gran extensió espacial d’aquest mapa, s’ha desenvolupat una plataforma web per facilitar-ne la visualització i millorar l’accessibilitat de la informació per a tots els usuaris. Com a pas addicional per millorar l’anàlisi, s’han integrat dades complementàries. El mapa BDD s’ha combinat amb la velocitat de deformació, l’antiguitat dels edificis (considerada com un indicador de vulnerabilitat) i dades de població, amb la finalitat de proporcionar una primera avaluació de l’impacte potencial sobre els residents. Aquesta integració ha donat lloc al desenvolupament d’un “Mapa d’Impacte Potencial”, que permet identificar àrees que requereixen atenció prioritària i recursos per a una mitigació eficaç del risc.
La robustesa de la metodologia proposada s’ha avaluat mitjançant un procediment específic de validació. Aquesta avaluació ha analitzat tant la metodologia com els seus resultats sota diferents geometries d’adquisició, demostrant que el gradient espacial de deformació és independent de la geometria, així com sota diferents intervals temporals. Així mateix, la validació s’ha complementat amb campanyes de camp per avaluar els danys en edificis, centrant-se en indicadors de deformació diferencial, com esquerdes i fissures en parets i al voltant de finestres.
(Español) La investigación de la deformación de edificios debida a asentamientos diferenciales es una tarea compleja, especialmente en áreas extensas; sin embargo, con el avance de las técnicas de teledetección, este tipo de estudios se ha vuelto actualmente viable. El European Ground Motion Service (EGMS), como parte del Copernicus Land Monitoring Service, representa el mayor servicio de Interferometría SAR (InSAR) a gran escala desarrollado hasta la fecha. Gracias a sus características técnicas y a la disponibilidad abierta y gratuita de sus productos, el EGMS facilita el acceso a mapas de desplazamiento. El desafío ahora reside en desarrollar metodologías y herramientas adecuadas para aprovechar eficazmente esta gran cantidad de información y generar mapas fáciles de interpretar, orientados a la evaluación del daño en edificios y a la mitigación del riesgo urbano.
Esta tesis doctoral aborda este desafío mediante la propuesta de una metodología y una herramienta de software innovadora que transforman los datos de desplazamiento derivados de InSAR en mapas geoespaciales completos, a través de un análisis de deformación diferencial espacial a escala de edificio. Esto permite la identificación y clasificación de edificios urbanos susceptibles a sufrir daños debido a movimientos diferenciales. En particular, se pone el foco en la deformación diferencial espacial (es decir, el gradiente espacial de deformación) a nivel individual de edificio, ya que la mayoría de los daños significativos en estructuras e infraestructuras están asociados a gradientes espaciales de deformación. El resultado final de la metodología propuesta es el denominado “Mapa de Deformación Diferencial de Edificios” (BDD). Esta metodología es novedosa porque, a diferencia de estudios previos centrados principalmente en áreas reducidas, permite la cartografía sobre áreas estensas manteniendo un análisis detallado a nivel de edificio. La metodología requiere únicamente dos tipos de datos de entrada: mapas de desplazamiento derivados de InSAR, independientemente de la fuente de datos, y un mapa vectorial de la huella de los edificios.
Este trabajo ilustra el uso de los productos básicos de EGMS para realizar un análisis multiescala, incluyendo la área metropolitana de Barcelona, la región de Cataluña y, finalmente, el mapa BDD de toda España. Dicho mapa incluye 2.958 edificios vulnerables a sufrir daños debido a asentamientos diferenciales. Dada la gran extensión espacial de este mapa, se ha desarrollado una plataforma web para facilitar su visualización y mejorar la accesibilidad de la información para todos los usuarios. Como paso adicional para mejorar el análisis, se han integrado datos complementarios. El mapa BDD se ha combinado con la velocidad de deformación, la antigüedad de los edificios (considerada como un indicador de vulnerabilidad) y datos de población, con el fin de proporcionar una primera evaluación del impacto potencial sobre los residentes. Esta integración ha dado lugar al desarrollo de un “Mapa de Impacto Potencial”, que permite identificar áreas que requieren atención prioritaria y recursos para una mitigación eficaz del ri
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.
Ehsan Sadeghian, D. Cusson, E. Dragomirescu et al.· e-Journal of Nondestructive...· 0 citations
Spaceborne Synthetic Aperture Radar (SAR) is a non-contact remote sensing technology that detects surface deformation by analyzing the phase differences between radar images acquired over the same area at different times. Due to its extensive coverage, high spatial resolution, and all-weather operational capability, spaceborne SAR has become an established technique for large-scale, continuous monitoring of civil infrastructure. Transportation networks constitute a fundamental component of urban infrastructure, playing a pivotal role in enabling efficient mobility and fostering regional economic development. Extreme weather events severely threaten the durability and operational safety of transportation networks. However, limited funding restricts the deployment of traditional sensors for detailed and comprehensive monitoring of the entire transportation network system. In this research, a stack of Sentinel SAR images acquired over a two-years period is collected from the Copernicus Data Space Ecosystem, and subsequently processed with Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) technology. A dedicated post-processing procedure, consisting of PS points refinement and clustering analysis, is applied to the displacement time series derived from the PS-InSAR processing. Then, statistical control limits method is employed to evaluate the risk levels across transportation network. Finally, the reliability and effectiveness of the proposed risk assessment framework are validated through a specific bridge case study. These findings demonstrate the potential of the proposed framework for large-scale, risk-informed assessment of transportation networks, thereby contributing to more proactive and data-driven transportation network management strategies.
Yi Xu, You Dong, Yi-qing Ni· e-Journal of Nondestructive...· 0 citations
Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) has matured into a credible, non-contact technique for monitoring bridge deformation from individual structures to regional portfolios. The main challenge for routine engineering use is no longer measuring millimetre-scale line-of-sight (LOS) displacement, but interpreting those measurements into defensible statements about structural condition. This review addresses that interpretation problem by synthesising the physical and algorithmic fundamentals of MT-InSAR, bridge-typology-dependent applicability, LOS projection ambiguity, current sensor capabilities, and emerging open data services. Particular emphasis is placed on signal decoupling because measured bridge displacement combines reversible thermal response, transient live-load effects, progressive deformation associated with damage or settlement, and measurement noise. Two complementary interpretation strategies are examined: physics-based integration using finite-element analysis, model updating and digital twins, and data-driven integration using clustering, anomaly detection, forecasting and deep learning. Their convergence through physics-informed methods is also discussed. The review proposes a hybrid framework in which data-driven methods screen bridge portfolios and identify anomalous deformation, while physics-based modelling provides structural interpretation and supports validation using inspection records, in-situ measurements and uncertainty quantification. The synthesis highlights the strengths and limitations of current practice and identifies research needs in multi-geometry analysis, dense spatial sampling, physics-informed learning, portfolio-scale digital twins and prospective validation. The resulting framework is intended to support scalable, physically interpretable and evidence-based use of MT-InSAR in bridge structural health monitoring.
