Exploring Problems and Prospective of Satellite Interferometric Data for the Seismic Structural Health Monitoring of Existing Buildings and Architectural Heritage

Satellite interferometric data represent a promising source of information for the Structural Health Monitoring (SHM) of the existing built environment. This is especially true because they show differential temporal-spatial displacements of remotely monitored points, which can be easily interpreted with a visual inspection of their time-histories for different locations defined a priori. However, the interferometric information is commonly referred to extended territories (at the scale of city or region), thus several problems arise in the implementation of automatic SHM techniques for the damage detection, localization, and assessment of the built environment at a point level (scale of the building or lower). Despite a long list of challenges, interferometric data have also the potential to become a useful source to assess the health of a structure, especially for helping in define structural early warning methodologies. For this reason, in the paper, the authors summarize the main challenges in the use of satellite interferometric data for civil SHM, and rather than proposing remedial actions, try to critically analyze the challenges and perspectives for future applications

Anticipating the collapse of urban infrastructure: a methodology based on Earth Observation and MT-InSAR

Large-scale infrastructure monitoring and vulnerability assessment are crucial for the preservation and maintenance of built environments. To ensure the safety of urban infrastructure against natural and man-made disasters, constant monitoring is crucial. To do so, satellite Earth observation (EO) is being proposed, particularly radar-based imaging, because it allows large-scale constant monitoring since radar signals are not blocked by clouds and can be collected during both day and night. The proposed methodology for large-scale infrastructure monitoring and vulnerability assessment is based on MT-InSAR time series analysis. The homogeneity of the year-to-year displacement trend between each point and its surrounding points is evaluated to determine whether the area is a stable or vulnerable zone. To validate the methodology, four case studies of recently collapsed infrastructures are analyzed. The results indicate the potential of the proposed methodology for predicting and preventing structural collapses.Ministerio de Ciencia e Innovación | Ref. PID2021-124236OB-C3

ADAtools: Automatic Detection and Classification of Active Deformation Areas from PSI Displacement Maps

This work describes the set of tools developed, tested, and put into production in the context of the H2020 project Multi-scale Observation and Monitoring of Railway Infrastructure Threats (MOMIT). This project, which ended in 2019, aimed to show how the use of various remote sensing techniques could help to improve the monitoring of railway infrastructures, such as tracks or bridges, and thus, consequently, improve the detection of ground instabilities and facilitate their management. Several lines of work were opened by MOMIT, but the authors of this work concentrated their efforts in the design of tools to help the detection and identification of ground movements using synthetic aperture radar interferometry (InSAR) data. The main output of this activity was a set of tools able to detect the areas labelled active deformation areas (ADA), with the highest deformation rates and to connect them to a geological or anthropogenic process. ADAtools is the name given to the aforementioned set of tools. The description of these tools includes the definition of their targets, inputs, and outputs, as well as details on how the correctness of the applications was checked and on the benchmarks showing their performance. The ADAtools include the following applications: ADAfinder, los2hv, ADAclassifier, and THEXfinder. The toolset is targeted at the analysis and interpretation of InSAR results. Ancillary information supports the semi-automatic interpretation and classification process. Two real use-cases illustrating this statement are included at the end of this paper to show the kind of results that may be obtained with the ADAtools.This work has received funding from the Shift2Rail Joint Undertaking under the European Union's Horizon 2020 research and innovation programme, with grant agreement No 777630, project MOMIT, “Multi-scale Observation and Monitoring of railway Infrastructure Threats”. It has been also partially funded by Interreg-Sudoe program of the EU, through the project RISKCOAST (Ref: SOE3/P4/E0868)

Interferometric Satellite Data in Structural Health Monitoring: An Application to the Effects of the Construction of a Subway Line in the Urban Area of Rome

In recent years, the use of interferometric satellite data for Structural Health Monitoring has experienced a strong development. The urban environment confirms its fragility to adverse natural events, made even more severe by climate change. Hence, the need to carry out continuous monitoring of structures and artefacts appears increasingly urgent. Furthermore, satellite data could considerably increase the feasibility of traditional Structural Health Monitoring (SHM) approaches.This study aims to explore this remote sensing approach, focusing on the representation techniques that can be adopted to highlight their advantages and provide an interpretation of the results. In particular, the study analyzes records from the urban area of Rome (Italy), subject to the construction of a new subway line. These data are exploited to create a velocity map to highlight the possible subsidence phenomenon induced by excavations. Then, the paper focuses on single buildings or building complexes through the entropy–energy representation. Beyond the different limitations caused by the input data, a correlation is identified between the results of the two representation techniques. Accordingly, the effects of excavation on the urban area are demonstrated, and the methodologies are validated

Monitoring the impact of groundwater pumping on infrastructure using Geographic Information System (GIS) and Persistent Scatterer Interferometry (PSI)

Transportation infrastructure is critical for the advancement of society. Bridges are vital for an efficient transportation network. Bridges across the world undergo variable deformation/displacement due to the Earth’s dynamic processes. This displacement is caused by ground motion, which occurs from many natural and anthropogenic events. Events causing deformation include temperature fluctuation, subsidence, landslides, earthquakes, water/sea level variation, subsurface resource extraction, etc. Continual deformation may cause bridge failure, putting civilians at risk, if not managed properly. Monitoring bridge displacement, large and small, provides evidence of the state and health of the bridge. Traditionally, bridge monitoring has been executed through on-site surveys. Although this method of bridge monitoring is systematic and successful, it is not the most efficient and cost-effective. Through technological advances, satellite-based Persistent Scatterer Interferometry (PSI) and Geographic Information Systems (GIS) have provided a system for analyzing ground deformation over time. This method is applied to distinguish bridges that are more at risk than others by generating models that display the displacement at various locations along each bridge. A bridge’s health and its potential risk can be estimated upon analysis of measured displacement rates. In return, this process of monitoring bridges can be done at much faster rates; saving time, money and resources. PSI data covering Oxnard, California, revealed both bridge displacement and regional ground displacement. Although each bridge maintained different patterns of displacement, many of the bridges within the Oxnard area displayed an overall downward movement matching regional subsidence trends observed in the area. Patterns in displacement-time series plots provide evidence for two types of deformation mechanisms. Long-term downward movements correlate with the relatively large regional subsidence observed using PSI in Oxnard. Thermal dilation from seasonal temperature changes may cause short-term variabilities unique to each bridge. Overall, it may be said that linking geologic, weather, and groundwater patterns with bridge displacement has shown promise for monitoring transportation infrastructure and more importantly differentiating between regional subsidence and site-specific displacements

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

Advanced exploitation of Sentinel-1 data for supporting landslide risk analysis

Tesi en modalitat de compendi de publicacionsSatellite Synthetic Aperture Radar Interferometry (InSAR) and Persistent Scatterer Interferometry (PSI) are now consolidated tools for ground movement detection and monitoring. Sentinel-1 (S1) is the first satellite providing free data access and ensuring a regular acquisition worldwide, every 6 days, increasing its potential for long-term monitoring applications. Several regional and national ground motion services are already active, providing products based on S1 data. Soon in 2022 the first European Ground Motion Service (EGMS) will be available and freely provide a displacement map over the whole Europe, with annual updates. This implies a strong expansion of availability of PSI-based displacement maps and an easy access for anyone, with an increasing interest among a wider range of users, including public or governmental institutions, academia, industry, and citizens. The analysis and interpretation of this amount of data is difficult and time consuming, mostly for non-expert InSAR users. The objective of this work is developing methodologies to simplify the operational use of PSI displacement maps, generating derived products with a clear message, easy-to-interpret, and fast to read. We propose a method to be applied over regional scale PSI displacement maps, to fast detect the most significant Active Deformation Areas (ADAs). The ADA map is a first product that allows a fast focusing on the active areas, to prioritize further analysis and investigation. Starting from the ADAs, the potential phenomena are attributed to each area through a preliminary interpretation based on auxiliary data, to derive the Geohazard Activity Map. In this work, a methodology to include the ADA information in the Civil Protection Activities is proposed, with the main output called Vulnerable Elements Activity Maps (VEAM). An application of the VEAM is illustrated in the Canary Islands. Furthermore, the ADA map is used in the Valle d'Aosta Region (Northern of Italy) to generate vulnerability and potential loss maps. Finally, a methodology to derive potential damage maps of the exposed buildings, based on the spatial gradients of movement, is proposed, and applied in a coastal area of the Province of Granada (Spain). A pack of software tools has been developed based on the proposed methods to extract ADA and then classify them to generate a Geohazard Activity Map. The set of tools is called ADATools, it is open-access, easy to use and fast, improving the operational exploitation of PSI regional-scale displacement maps. All the methodologies have been developed in the frame of several European projects (Safety, U-Geohaz, MOMIT and RISKCOAST), and are aimed at supporting the multi-scale territorial management and risk analysis activities, with a specific focus on landslides.La interferometría satelital radar (InSAR) y la interferometría de dispersores persistentes (PSI) son herramientas consolidadas para la detección y el monitoreo de movimientos de la superficie de la Tierra. Sentinel-1 (S1) es el primer satélite que proporciona acceso gratuito a los datos y garantiza una adquisición regular en todo el mundo, cada 6 días, aumentando su potencial para aplicaciones de monitoreo a largo plazo. Varios Ground Motion Services regionales y nacionales ya están activos, proporcionando productos basados en datos S1. Pronto, en 2022, el primer servicio europeo (European Ground Motion Service - EGMS) estará disponible y facilitará libremente un mapa de movimientos de toda Europa, con actualizaciones anuales. Esto implica un aumento de la disponibilidad de mapas de movimientos basados en PSI y un fácil acceso para cualquier persona, con un interés creciente entre una amplia gama de usuarios, incluyendo instituciones públicas o gubernamentales, academias, industrias y ciudadanos. El análisis e interpretación de esta cantidad de datos es difícil y consume mucho tiempo, mayormente para usuarios no expertos en la técnica. El objetivo de este trabajo es desarrollar metodologías para simplificar el uso operativo de los mapas de desplazamiento PSI, generando productos derivados con un mensaje claro, fácil de interpretar, y rápido de leer. Se propone un método para detectar rápidamente las Áreas de Deformación Activas (ADAs) más significativas, a partir de mapas de desplazamiento PSI de escala regional. El mapa de las ADAs es un primer producto que permite un enfoque rápido en las áreas activas, útil para priorizar el análisis y las investigaciones adicionales. A partir de las ADAs, se propone una interpretación preliminar basada en datos auxiliares, que atribuye a cada área el fenómeno que está detrás del movimiento, generando el Geohazard Activity Map (GAM). Después, se propone una metodología para incluir la información de las ADAs en las actividades de protección civil, generando los Vulnerable Element Activity Maps (VEAM), a través de su aplicación en las Islas Canarias. Además, el mapa de las ADAs se utiliza en la región de Valle D'Aosta (norte de Italia) para generar mapas de vulnerabilidad y posibles pérdidas económicas. Finalmente, se propone una metodología para obtener mapas de daños potenciales de los edificios expuestos, basados en los gradientes espaciales de movimiento, y se aplica en un área costera de la provincia de Granada (España). A partir de los métodos propuestos para extraer y clasificar las ADAs, y de otros métodos de análisis existentes, se ha desarrollado un paquete de herramientas, los ADAtools, de acceso abierto, fáciles de usar y rápidas, que optimizan la explotación operativa de los mapas de desplazamiento de escala regional. Todas las metodologías se han desarrollado en el marco de varios proyectos europeos (Safety, U-Geohaz, MOMIT y RISKCOAST), y están dirigidos a apoyar las actividades de gestión territorial y análisis de riesgos, con un enfoque específico a los deslizamientos de tierra.Postprint (published version

Advanced exploitation of Sentinel-1 data for supporting landslide risk analysis

Tesi en modalitat de compendi de publicacionsSatellite Synthetic Aperture Radar Interferometry (InSAR) and Persistent Scatterer Interferometry (PSI) are now consolidated tools for ground movement detection and monitoring. Sentinel-1 (S1) is the first satellite providing free data access and ensuring a regular acquisition worldwide, every 6 days, increasing its potential for long-term monitoring applications. Several regional and national ground motion services are already active, providing products based on S1 data. Soon in 2022 the first European Ground Motion Service (EGMS) will be available and freely provide a displacement map over the whole Europe, with annual updates. This implies a strong expansion of availability of PSI-based displacement maps and an easy access for anyone, with an increasing interest among a wider range of users, including public or governmental institutions, academia, industry, and citizens. The analysis and interpretation of this amount of data is difficult and time consuming, mostly for non-expert InSAR users. The objective of this work is developing methodologies to simplify the operational use of PSI displacement maps, generating derived products with a clear message, easy-to-interpret, and fast to read. We propose a method to be applied over regional scale PSI displacement maps, to fast detect the most significant Active Deformation Areas (ADAs). The ADA map is a first product that allows a fast focusing on the active areas, to prioritize further analysis and investigation. Starting from the ADAs, the potential phenomena are attributed to each area through a preliminary interpretation based on auxiliary data, to derive the Geohazard Activity Map. In this work, a methodology to include the ADA information in the Civil Protection Activities is proposed, with the main output called Vulnerable Elements Activity Maps (VEAM). An application of the VEAM is illustrated in the Canary Islands. Furthermore, the ADA map is used in the Valle d'Aosta Region (Northern of Italy) to generate vulnerability and potential loss maps. Finally, a methodology to derive potential damage maps of the exposed buildings, based on the spatial gradients of movement, is proposed, and applied in a coastal area of the Province of Granada (Spain). A pack of software tools has been developed based on the proposed methods to extract ADA and then classify them to generate a Geohazard Activity Map. The set of tools is called ADATools, it is open-access, easy to use and fast, improving the operational exploitation of PSI regional-scale displacement maps. All the methodologies have been developed in the frame of several European projects (Safety, U-Geohaz, MOMIT and RISKCOAST), and are aimed at supporting the multi-scale territorial management and risk analysis activities, with a specific focus on landslides.La interferometría satelital radar (InSAR) y la interferometría de dispersores persistentes (PSI) son herramientas consolidadas para la detección y el monitoreo de movimientos de la superficie de la Tierra. Sentinel-1 (S1) es el primer satélite que proporciona acceso gratuito a los datos y garantiza una adquisición regular en todo el mundo, cada 6 días, aumentando su potencial para aplicaciones de monitoreo a largo plazo. Varios Ground Motion Services regionales y nacionales ya están activos, proporcionando productos basados en datos S1. Pronto, en 2022, el primer servicio europeo (European Ground Motion Service - EGMS) estará disponible y facilitará libremente un mapa de movimientos de toda Europa, con actualizaciones anuales. Esto implica un aumento de la disponibilidad de mapas de movimientos basados en PSI y un fácil acceso para cualquier persona, con un interés creciente entre una amplia gama de usuarios, incluyendo instituciones públicas o gubernamentales, academias, industrias y ciudadanos. El análisis e interpretación de esta cantidad de datos es difícil y consume mucho tiempo, mayormente para usuarios no expertos en la técnica. El objetivo de este trabajo es desarrollar metodologías para simplificar el uso operativo de los mapas de desplazamiento PSI, generando productos derivados con un mensaje claro, fácil de interpretar, y rápido de leer. Se propone un método para detectar rápidamente las Áreas de Deformación Activas (ADAs) más significativas, a partir de mapas de desplazamiento PSI de escala regional. El mapa de las ADAs es un primer producto que permite un enfoque rápido en las áreas activas, útil para priorizar el análisis y las investigaciones adicionales. A partir de las ADAs, se propone una interpretación preliminar basada en datos auxiliares, que atribuye a cada área el fenómeno que está detrás del movimiento, generando el Geohazard Activity Map (GAM). Después, se propone una metodología para incluir la información de las ADAs en las actividades de protección civil, generando los Vulnerable Element Activity Maps (VEAM), a través de su aplicación en las Islas Canarias. Además, el mapa de las ADAs se utiliza en la región de Valle D'Aosta (norte de Italia) para generar mapas de vulnerabilidad y posibles pérdidas económicas. Finalmente, se propone una metodología para obtener mapas de daños potenciales de los edificios expuestos, basados en los gradientes espaciales de movimiento, y se aplica en un área costera de la provincia de Granada (España). A partir de los métodos propuestos para extraer y clasificar las ADAs, y de otros métodos de análisis existentes, se ha desarrollado un paquete de herramientas, los ADAtools, de acceso abierto, fáciles de usar y rápidas, que optimizan la explotación operativa de los mapas de desplazamiento de escala regional. Todas las metodologías se han desarrollado en el marco de varios proyectos europeos (Safety, U-Geohaz, MOMIT y RISKCOAST), y están dirigidos a apoyar las actividades de gestión territorial y análisis de riesgos, con un enfoque específico a los deslizamientos de tierra.Enginyeria del terren

Advances on the investigation of landslides by space-borne synthetic aperture radar interferometry

Landslides are destructive geohazards to people and infrastructure, resulting in hundreds of deaths and billions of dollars of damage every year. Therefore, mapping the rate of deformation of such geohazards and understanding their mechanics is of paramount importance to mitigate the resulting impacts and properly manage the associated risks. In this paper, the main outcomes relevant to the joint European Space Agency (ESA) and the Chinese Ministry of Science and Technology (MOST) Dragon-5 initiative cooperation project ID 59,339 “Earth observation for seismic hazard assessment and landslide early warning system” are reported. The primary goals of the project are to further develop advanced SAR/InSAR and optical techniques to investigate seismic hazards and risks, detect potential landslides in wide regions, and demonstrate EO-based landslide early warning system over selected landslides. This work only focuses on the landslide hazard content of the project, and thus, in order to achieve these objectives, the following tasks were developed up to now: a) a procedure for phase unwrapping errors and tropospheric delay correction; b) an improvement of a cross-platform SAR offset tracking method for the retrieval of long-term ground displacements; c) the application of polarimetric SAR interferometry (PolInSAR) to increase the number and quality of monitoring points in landslide-prone areas; d) the semiautomatic mapping and preliminary classification of active displacement areas on wide regions; e) the modeling and identification of landslides in order to identify triggering factors or predict future displacements; and f) the application of an InSAR-based landslide early warning system on a selected site. The achieved results, which mainly focus on specific sensitive regions, provide essential assets for planning present and future scientific activities devoted to identifying, mapping, characterizing, monitoring and predicting landslides, as well as for the implementation of early warning systems.This work was supported by the ESA-MOST China DRAGON-5 project with ref. 59339, by the Spanish Ministry of Science and Innovation, the State Agency of Research (AEI), and the European Funds for Regional Development under grant [grant number PID2020-117303GB-C22], by the Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital in the framework of the project CIAICO/2021/335, by the Natural Science Foundation of China [grant numbers 41874005 and 41929001], the Fundamental Research Funds for the Central University [grant numbers 300102269712 and 300102269303], and China Geological Survey Project [grant numbers DD20190637 and DD20190647]. Xiaojie Liu and Liuru Hu have been funded by Chinese Scholarship Council Grants Ref. [grant number 202006560031] and [grant number 202004180062], respectively