Railways’ Stability Observation by Satellite Radar Images

Remote sensing has many vital civilian applications. Space-borne Interferometric Synthetic Aperture Radar has been used to measure the Earth’s surface deformation widely. In particular, Persistent Scatterer Interferometry (PSI) is designed to estimate the temporal characteristics of the Earth’s deformation rates from multiple InSAR images acquired over time. This chapter reviews the space-borne Differential Interferometric Synthetic Aperture Radar techniques that have shown their capabilities in monitoring of railways displacements. After description of the current state of the art and potentials of the available radar remote sensing techniques, one case study is examined, pertaining to a railway bridge in the Campania region, Italy

DEFORMATION MONITORING OF LARGE STRUCTURES BY GROUND-BASED SAR INTERFEROMETRY

In this paper, a ground-based SAR interferometry technology was used to monitor major engineering. This technology has been recognized as a powerful tool for terrain monitoring and structural change detecting. Deformation monitoring for large project has been a hot issue among them. According to GBSAR interferometry principle and characteristics of IBIS system, the authors analysis the error sources of deformation monitoring, and experimentally extract atmospheric phase which should removed based on permanent scattered analysis. Atmospheric disturbance effect analysis is discussed in this paper, and an atmospheric correction method is proposed to remove atmospheric effect, then the effective displacement can be retrieved. Results from this approach have been compared with that from traditional method in this campaign, GBInSAR technology can be exploited successfully in deformation monitoring for major projects with high accuracy

Monitoring deformations of infrastructure networks:A fully automated GIS integration and analysis of InSAR time-series

Ageing stock and extreme weather events pose a threat to the safety of infrastructure networks. In most countries, funding allocated to infrastructure management is insufficient to perform systematic inspections over large transport networks. As a result, early signs of distress can develop unnoticed, potentially leading to catastrophic structural failures. Over the past 20 years, a wealth of literature has demonstrated the capability of satellite-based Synthetic Aperture Radar Interferometry (InSAR) to accurately detect surface deformations of different types of assets. Thanks to the high accuracy and spatial density of measurements, and a short revisit time, space-borne remote-sensing techniques have the potential to provide a cost-effective and near real-time monitoring tool. Whilst InSAR techniques offer an effective approach for structural health monitoring, they also provide a large amount of data. For civil engineering procedures, these need to be analysed in combination with large infrastructure inventories. Over a regional scale, the manual extraction of InSAR-derived displacements from individual assets is extremely time-consuming and an automated integration of the two datasets is essential to effectively assess infrastructure systems. This paper presents a new methodology based on the fully automated integration of InSAR-based measurements and Geographic Information System-infrastructure inventories to detect potential warnings over extensive transport networks. A Sentinel dataset from 2016 to 2019 is used to analyse the Los Angeles highway and freeway network, while the Italian motorway network is evaluated by using open access ERS/Envisat datasets between 1992 and 2010, COSMO-SkyMed datasets between 2008 and 2014 and Sentinel datasets between 2014 and 2020. To demonstrate the flexibility of the proposed methodology to different SAR sensors and infrastructure classes, the analysis of bridges and viaducts in the two test areas is also performed. The outcomes highlight the potential of the proposed methodology to be integrated into structural health monitoring systems and improve current procedures for transport network management.</p

Urban Deformation Monitoring using Persistent Scatterer Interferometry and SAR tomography

This book focuses on remote sensing for urban deformation monitoring. In particular, it highlights how deformation monitoring in urban areas can be carried out using Persistent Scatterer Interferometry (PSI) and Synthetic Aperture Radar (SAR) Tomography (TomoSAR). Several contributions show the capabilities of Interferometric SAR (InSAR) and PSI techniques for urban deformation monitoring. Some of them show the advantages of TomoSAR in un-mixing multiple scatterers for urban mapping and monitoring. This book is dedicated to the technical and scientific community interested in urban applications. It is useful for choosing the appropriate technique and gaining an assessment of the expected performance. The book will also be useful to researchers, as it provides information on the state-of-the-art and new trends in this fiel

Building deformation assessment by means of Persistent Scatterer Interferometry analysis on a landslide-affected area: the Volterra (Italy) case study

In recent years, space-borne InSAR (interferometric synthetic aperture radar) techniques have shown their capabilities to provide precise measurements of Earth surface displacements for monitoring natural processes. Landslides threaten human lives and structures, especially in urbanized areas, where the density of elements at risk sensitive to ground movements is high. The methodology described in this paper aims at detecting terrain motions and building deformations at the local scale, by means of satellite radar data combined with in situ validation campaigns. The proposed approach consists of deriving maximum settlement directions of the investigated buildings from displacement data revealed by radar measurements and then in the cross-comparison of these values with background geological data, constructive features and on-field evidence. This validation permits better understanding whether or not the detected movements correspond to visible and effective damages to buildings. The method has been applied to the southwestern sector of Volterra (Tuscany region, Italy), which is a landslide-affected and partially urbanized area, through the use of COSMO-SkyMed satellite images as input data. Moreover, we discuss issues and possible misinterpretations when dealing with PSI (Persistent Scatterer Interferometry) data referring to single manufactures and the consequent difficulty of attributing the motion rate to ground displacements, rather than to structural failures

Bridge Monitoring Strategies for Sustainable Development with Microwave Radar Interferometry

The potential of a coherent microwave radar for infrastructure health monitoring has been investigated over the past decade. Microwave radar measuring based on interferometry processing is a non-invasive technique that can measure the line-of-sight (LOS) displacements of large infrastructure with sub-millimeter precision and provide the corresponding frequency spectrum. It has the capability to estimate infrastructure vibration simultaneously and remotely with high accuracy and repeatability, which serves the long-term serviceability of bridge structures within the context of the long-term sustainability of civil engineering infrastructure management. In this paper, we present three types of microwave radar systems employed to monitor the displacement of bridges in Japan and Italy. A technique that fuses polarimetric analysis and the interferometry technique for bridge monitoring is proposed. Monitoring results achieved with full polarimetric real aperture radar (RAR), step-frequency continuous-wave (SFCW)-based linear synthetic aperture, and multi-input multi-output (MIMO) array sensors are also presented. The results reveal bridge dynamic responses under different loading conditions, including wind, vehicular traffic, and passing trains, and show that microwave sensor interferometry can be utilized to monitor the dynamics of bridge structures with unprecedented spatial and temporal resolution. This paper demonstrates that microwave sensor interferometry with efficient, cost-effective, and non-destructive properties is a serious contender to employment as a sustainable infrastructure monitoring technology serving the sustainable development agenda

Integration of remote sensing and ground-based non-destructive methods in transport infrastructure monitoring: advances, challenges and perspectives

High temporal frequency monitoring of transport infrastructures is crucial for implementing effective maintenance prioritisation strategies and prevent major failures. To this extent, ground-based non-destructive testing (NDT) methods have been successfully applied for decades, reaching very high standards of data quality and accuracy. However, routine and systematic campaigns are required over relatively long inspection times for data collection and implementation into reliable infrastructure management systems (IMSs). On the other hand, satellite remote sensing techniques, such as the Multi-Temporal Interferometric Synthetic Aperture Radar (MT-InSAR) method, have proven effective in monitoring ground displacements of transport infrastructures (roads, railways and airfields), with a much higher temporal frequency of investigation and wider inspection catchment areas. Nevertheless, the integration of information from i) satellite remote sensing and ii) ground-based NDT methods is still an area to be explored in civil engineering. Within this framework, this paper aims to review significant stand-alone applications in these two areas of technology for transport infrastructure monitoring. Furthermore, recent advances, main challenges and future perspectives arising from their integration are discussed. Contents of this paper are organised within the context of an invited keynote talk given at the 2021 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing (AGERS – 2021)

Ground-based synthetic aperture radar (GBSAR) interferometry for deformation monitoring

Ph. D ThesisGround-based synthetic aperture radar (GBSAR), together with interferometry, represents a powerful tool for deformation monitoring. GBSAR has inherent flexibility, allowing data to be collected with adjustable temporal resolutions through either continuous or discontinuous mode. The goal of this research is to develop a framework to effectively utilise GBSAR for deformation monitoring in both modes, with the emphasis on accuracy, robustness, and real-time capability. To achieve this goal, advanced Interferometric SAR (InSAR) processing algorithms have been proposed to address existing issues in conventional interferometry for GBSAR deformation monitoring. The proposed interferometric algorithms include a new non-local method for the accurate estimation of coherence and interferometric phase, a new approach to selecting coherent pixels with the aim of maximising the density of selected pixels and optimizing the reliability of time series analysis, and a rigorous model for the correction of atmospheric and repositioning errors. On the basis of these algorithms, two complete interferometric processing chains have been developed: one for continuous and the other for discontinuous GBSAR deformation monitoring. The continuous chain is able to process infinite incoming images in real time and extract the evolution of surface movements through temporally coherent pixels. The discontinuous chain integrates additional automatic coregistration of images and correction of repositioning errors between different campaigns. Successful deformation monitoring applications have been completed, including three continuous (a dune, a bridge, and a coastal cliff) and one discontinuous (a hillside), which have demonstrated the feasibility and effectiveness of the presented algorithms and chains for high-accuracy GBSAR interferometric measurement. Significant deformation signals were detected from the three continuous applications and no deformation from the discontinuous. The achieved results are justified quantitatively via a defined precision indicator for the time series estimation and validated qualitatively via a priori knowledge of these observing sites.China Scholarship Council (CSC), Newcastle Universit

Using InSAR stacking techniques to predict bridge collapse due to scour

Failure of bridges due to scour is of great concern to bridge asset owners, and is currently very difficult to predict and monitor regularly using conventional assessment methods. This paper presents evidence of how InSAR techniques can be used to monitor bridges at risk of scour, using Tadcaster Bridge, England, as a case study. Tadcaster Bridge suffered a partial collapse due to river scour on the evening of December 29th, 2015 following a period of severe rainfall and flooding. SAR scenes over the bridge from the two-year period prior to the collapse are analysed using SBAS interferometry methods, highlighting a distinct movement in the region of the bridge where the collapse occurred prior to the actual event. This precursor to failure observed in the data suggests the possible use of InSAR in structural health monitoring of bridges at risk of scour, as a means of an early warning system