Structural health monitoring of engineered structures using a space-borne synthetic aperture radar multi-temporal approach: from cultural heritage sites to war zones

Structural health monitoring (SHM) of engineered structures consists of an automated or semi-automated survey system that seeks to assess the structural condition of an anthropogenic structure. The aim of an SHM system is to provide insights into possible induced damage or any inherent signals of deformation affecting the structure in terms of detection, localization, assessment, and prediction. During the last decade there has been a growing interest in using several remote sensing techniques, such as synthetic aperture radar (SAR), for SHM. Constellations of SAR satellites with short repeat time acquisitions permit detailed surveys temporal resolution and millimetric sensitivity to deformation that are at the scales relevant to monitoring large structures. The all-weather multi-temporal characteristics of SAR make its products suitable for SHM systems, especially in areas where in situ measurements are not feasible or not cost effective. To illustrate this capability, we present results from COSMO-SkyMed (CSK) and TerraSAR-X SAR observations applied to the remote sensing of engineered structures. We show how by using multiple-geometry SAR-based products which exploit both phase and amplitude of the SAR signal we can address the main objectives of an SHM system including detection and localization. We highlight that, when external data such as rain or temperature records are available or simple elastic models can be assumed, the SAR-based SHM capability can also provide an interpretation in terms of assessment and prediction. We highlight examples of the potential for such imaging capabilities to enable advances in SHM from space, focusing on dams and cultural heritage areas. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only

The State of Remote Sensing Capabilities of Cascading Hazards Over High Mountain Asia

Cascading hazard processes refer to a primary trigger such as heavy rainfall, seismic activity, or snow melt, followed by a chain or web of consequences that can cause subsequent hazards influenced by a complex array of preconditions and vulnerabilities. These interact in multiple ways and can have tremendous impacts on populations proximate to or downstream of these initial triggers. High Mountain Asia (HMA) is extremely vulnerable to cascading hazard processes given the tectonic, geomorphologic, and climatic setting of the region, particularly as it relates to glacial lakes. Given the limitations of in situ surveys in steep and often inaccessible terrain, remote sensing data are a valuable resource for better understanding and quantifying these processes. The present work provides a survey of cascading hazard processes impacting HMA and how these can be characterized using remote sensing sources. We discuss how remote sensing products can be used to address these process chains, citing several examples of cascading hazard scenarios across HMA. This work also provides a perspective on the current gaps and challenges, community needs, and view forward toward improved characterization of evolving hazards and risk across HMA

Neural Network Pattern Recognition Experiments Toward a Fully Automatic Detection of Anomalies in InSAR Time Series of Surface Deformation

We present a neural network-based method to detect anomalies in time-dependent surface deformation fields given a set of geodetic images of displacements collected from multiple viewing geometries. The presented methodology is based on a supervised classification approach using combinations of line of sight multitemporal, multi-geometry interferometric synthetic aperture radar (InSAR) time series of displacements. We demonstrate this method with a set of 170 million time series of surface deformation generated for the entire Italian territory and derived from ERS, ENVISAT, and COSMO-SkyMed Synthetic Aperture Radar satellite constellations. We create a training dataset that has been compared with independently validated data and current state-of-the-art classification techniques. Compared to state-of-the-art algorithms, the presented framework provides increased detection accuracy, precision, recall, and reduced processing times for critical infrastructure and landslide monitoring. This study highlights how the proposed approach can accelerate the anomalous points identification step by up to 147 times compared to analytical and other artificial intelligence methods and can be theoretically extended to other geodetic measurements such as GPS, leveling data, or extensometers. Our results indicate that the proposed approach would make the anomaly identification post-processing times negligible when compared to the InSAR time-series processing

Satellite monitoring of harmful algal blooms (HABs) to protect the aquaculture industry

Harmful algal blooms (HABs) can cause sudden and considerable losses to fish farms, for example 500,000 salmon during one bloom in Shetland, and also present a threat to human health. Early warning allows the industry to take protective measures. PML's satellite monitoring of HABs is now funded by the Scottish aquaculture industry. The service involves processing EO ocean colour data from NASA and ESA in near-real time, and applying novel techniques for discriminating certain harmful blooms from harmless algae. Within the AQUA-USERS project we are extending this capability to further HAB species within several European countries

Applications of Satellite Earth Observations section - NEODAAS: Providing satellite data for efficient research

The NERC Earth Observation Data Acquisition and Analysis Service (NEODAAS) provides a central point of Earth Observation (EO) satellite data access and expertise for UK researchers. The service is tailored to individual users’ requirements to ensure that researchers can focus effort on their science, rather than struggling with correct use of unfamiliar satellite data

Multi-Temporal InSAR Structural Damage Assessment: The London Crossrail Case Study

Spaceborne multi-temporal interferometric synthetic aperture radar (MT-InSAR) is a monitoring technique capable of extracting line of sight (LOS) cumulative surface displacement measurements with millimeter accuracy. Several improvements in the techniques and datasets quality lead to more effective, near real time assessment and response, and a greater ability of constraining dynamically changing physical processes. Using examples of the COSMO-SkyMed (CSK) system, we present a methodology that bridges the gaps between MT-InSAR and the relative stiffness method for tunnel-induced subsidence damage assessment. The results allow quantification of the effect of the building on the settlement profile. As expected the greenfield deformation assessment tends to provide a conservative estimate in the majority of cases (~ 71% of the analyzed buildings), overestimating tensile strains up to 50%. With this work we show how these two techniques in the field of remote sensing and structural engineering can be synergistically used to complement and replace the traditional ground based analysis by providing an extended coverage and a temporally dense set of data

SAR Interferometry Data Exploitation for Infrastructure Monitoring Using GIS Application

Monitoring structural stability in urban areas and infrastructure networks is emerging as one of the dominant socio-economic issues for population security. The problem is accentuated by the age of the infrastructure because of increasing risks due to material deterioration and loss of load capacity. In this case, SAR satellite data are crucial to identify and assess the deteriorating conditions of civil infrastructures. The large amount of data available from SAR satellite sensors leads to the exploitation and development of new GIS-based procedures for rapid responses and decision making. In recent decades, the DInSAR technique has been used efficiently for the monitoring of structures, providing measurement points located on structures with millimeter precision. Our study has analyzed the behavior of structures in settlements, attempting to discuss the interactions of soil and structures, and examining the behavior of different types of structures, such as roads and buildings. The method used is based on long-term SAR interferometry data and a semi-automatic procedure to measure the displacement (mm/year) of structures, through a GIS-based application performed in the “Implemented MOnitoring DIsplacement” I.MODI platform. The analysis provides extensive information on long-term spatial and temporal continuity of up to 25 years of record, using satellite SAR multi-sensors from ERS, Envisat, and COSMO-SkyMed. The interpretation uses time series spatial analysis, supported by orthophotos, and layers of the DBTR (regional topographic database), Digital Surface model (DSM), and hydrogeological map to show anomalous areas with a high displacement rate and to observe the correlation of settlements in the sediments. With the satellite information and Geographic Information System (GIS), we were able to observe relevant parameters, such as the velocity of advance in the direction of the slope (deformation profiles), the cumulative displacement, and the trend changes in structures. The results illustrate an innovative procedure that allows the management of DInSAR data to facilitate the effective management of structures in which a monitoring protocol was developed at different spatial scales, integrating the information into a GIS

Monitoring of critical infrastructures by micro-motion estimation : the Mosul dam destabilization

In this paper, authors propose a new procedure to provide a tool for monitoring critical infrastructures. Particularly, through the analysis of COSMO-SkyMed satellite data, a detailed and updated survey is provided, for monitoring the accelerating destabilization process of the Mosul dam, that represents the largest hydraulic facility of Iraq and is located on the Tigris river. The destructive potential of the wave that would be generated, in the event of the dam destruction, could have serious consequences. If the concern for human lives comes first, the concern for cultural heritage protection is not negligible, since several archaeological sites are located around the Mosul dam. The proposed procedure is an in-depth modal assessment based on the micro-motion estimation, through a Doppler sub-apertures tracking and a Multi-Chromatic Analysis (MCA). The method is based initially on the Persistent Scatterers Interferometry (PSI) that is also discussed for completeness and validation. The modal analysis has detected the presence of several areas of resonance that could mean the presence of cracks, and the results have shown that the dam is still in a strong destabilization. Moreover, the dam appears to be divided into two parts: the northern part is accelerating rapidly while the southern part is decelerating and a main crack in this north-south junction is found. The estimated velocities through the PS-InSAR technique show a good agreement with the GNSS in-situ measurements, resulting in a very high correlation coefficient and showing how the proposed procedure works efficiently

Soil Moisture Estimation for landslide monitoring: A new approach using multi-temporal Synthetic Aperture RADAR data

This study explores the utility of the Spotlight2 X-band Synthetic Aperture Radar product developed by the Italian Space Agency for use in multi-temporal estimation of soil moisture in a landslide monitoring context, using a time series of monthly images of the Hollin Hill Landslide Observatory – North Yorkshire, UK. The study shows the complexity of surface soil moisture at an active landslide, using high resolution in situ soil moisture data. This in situ data is also used for ground truthing the soil moisture estimations from the SAR data. The study shows the limitations of inter-and intra-sensor calibration within the Cosmo-SkyMed array and contextualises this problem within the current research climate where SAR imagery is increasingly being created using multi-satellite constellation, while being used, increasingly, by environmental scientists rather than remote sensing specialists

A roadmap for high-resolution satellite soil moisture applications – confronting product characteristics with user requirements

Soil moisture observations are of broad scientific interest and practical value for a wide range of applications. The scientific community has made significant progress in estimating soil moisture from satellite-based Earth observation data, particularly in operationalizing coarse-resolution (25-50 km) soil moisture products. This review summarizes existing applications of satellite-derived soil moisture products and identifies gaps between the characteristics of currently available soil moisture products and the application requirements from various disciplines. We discuss the efforts devoted to the generation of high-resolution soil moisture products from satellite Synthetic Aperture Radar (SAR) data such as Sentinel-1 C-band backscatter observations and/or through downscaling of existing coarse-resolution microwave soil moisture products. Open issues and future opportunities of satellite-derived soil moisture are discussed, providing guidance for further development of operational soil moisture products and bridging the gap between the soil moisture user and supplier communities