Advances in Remote Sensing for Infrastructure Monitoring

This chapter provides a summary of the most current sensors being used for monitoring infrastructure. We also provide case studies on:

We have shown that high-resolution InSAR images are effective as an early warning system to monitor:

We have also shown that radar time-series, change detection, and polarmetric image fusion techniques are effective to identify

These case studies will assist in providing guidelines for the use of advanced radar image techniques for monitoring infrastructure related to civil engineering construction and mining.

Monitoring ground displacement due to natural or human-made processes is an issue of major importance for engineers and planners; increased knowledge of displacement benefits all involved. Satellite based Synthetic Aperture Radar (SAR) is a data source which when coupled with interferometric SAR (InSAR) techniques provides a powerful tool for estimating ground displacement. Vast areas can be mapped at spatial resolutions of a few metres with centimetre to millimetre displacement precision. SAR data archives exist for some areas as far back as the early 1990s. Since the arrival of modern sensors such as Sentinel-1, near global archives are being updated every few days and commonly reach back to 2015.

InSAR technology can seem complex and unwieldy to the unfamiliar. Measurements are one dimensional, satellite viewing geometry creates unintuitive effects, and several tradeoffs must be navigated to design a successful monitoring program. Potential users may feel reluctant to invest the effort required to feel comfortable with the technology, or may be discouraged by the technical jargon that persists in this field of practice. Others may be unsure whether the technology applies to their particular application or use case.

This work aims to provide readers with a means to gain familiarity with the technology and its applications. The chapter presents the topic in an easy to read manner, aimed at those who may be interested in initiating an archive analysis or an ongoing monitoring program for an area of interest. Key concepts are first presented, which will help readers understand the main considerations and limitations that are pertinent. Four case studies are then presented relating to tunnelling, aqueducts and aquifers, pipeline rights of way, and mining.

A continuous monitoring system of ground deformation, based on radar images acquired by ESA (European Space Agency) Sentinel-1 constellation, is active over the Tuscany Region (Central Italy). The potential of repeat-pass satellite SAR (Synthetic Aperture Radar) interferometry has been exploited to investigate spatial patterns and temporal evolution of regional and local ground deformation that affect man-made infrastructures. With one million of points for each geometry of acquisition, ground deformation maps for Tuscany Region provide information that can be exploited to scan wide areas and to flag ground instabilities. These areas become targets for detailed analysis with high-resolution sensors (e.g., COSMO-SkyMed satellites of the Italian Space Agency) to create a virtual constellation, in which different satellite data sources are synergically used to create a more effective and robust Earth observation system. The results obtained are presented and discussed through the case studies of Pistoia and Guasticce (Livorno), where land subsidence threatens linear and areal strategic infrastructures. The examples highlight the capability of radar satellite missions to provide regularly spatially continuous information, which are of fundamental importance for monitoring ground deformation caused by land subsidence.

Resilient railway transportation networks require sustainable, cost-effective management of service operations to meet future socio-economic needs and ensure the protection of the natural environment. Where transportation corridors traverse unstable terrain, critical rail infrastructure is at risk of damage and presents potential local and national economic, social and environmental challenges. Remote monitoring of unstable slopes and infrastructure at risk, using a range of conventional and emerging fixed and automated (i.e. remote) technologies provides the fundamental geoscience required to monitor landslides along a strategically important section of Canada’s national railway network in south-central British Columbia, Canada. Research and development by the Geological Survey of Canada and British Geological Survey provides government agencies, university partners and the national railway companies with vital information to understand geohazard risk, predict landslide movement, improve the safety, security and resilience of national transportation infrastructure, and reduce such risks to the economy, environment, natural resources and public safety.

Landslide, debris flow, and debris flood are the most common geological hazards triggered by intense rainfall in Taiwan. Taiwan is a very densely populated high relief island, and therefore the landslides sometimes affect our transportation and energy infrastructures and populated areas. This study investigates the regional landslide activity and potential slope movement using high-resolution time-series RADARSAT-2 InSAR images. We focussed on the 2015 typhoon, which affected Wulai and Xindian Districts in northern Taiwan. InSAR techniques, such as D-InSAR and SBAS, were applied to detect slope deformation caused by shallow and deep-seated landslides. This study conducted field investigations, and used high-resolution DTMs, and 3D photographic UAV surveying to determine the landslide hotspots and geomorphologic changes. The validation results show the InSAR maps accurately identify slow-moving landslides with a surface displacement of about 2 cm/year and debris flows on the bed of a gully. The InSAR displacement map helps to recognize the possible deep-seated landslides not previously known using a DTM. The field validation of the InSAR results from the proposed approach confirmed that the detection of different types of slope-land hazards: shallow landslides, deep-seated landslides, debris flows, and sediment deposition. Furthermore, the result will contribute to updating the national-wide environmental geologic map and provide competent authority to make decisions reducing the geohazard risk.

Tectonic and land surface processes deform and disturb infrastructure and urban environments. Several remote sensing techniques have been developed to measure and monitor these processes. Disasters also can damage or destroy infrastructure and urban environments and one disaster can cascade into subsequent disasters. This chapter discusses hazards and disasters affecting infrastructure. Applicable remote sensing methods and interfaces are described for accessing data and data products. The chapter then presents case studies that illustrate the use of the remote sensing data for various applications.

Public transportation agencies need reliable monitoring technologies to provide advance warnings of performance loss and potential pending failure of their valuable assets, probability of which may increase due to climate change and extreme weather events. To address this concern, a partnership was formed to validate an innovative monitoring approach that can measure bridge displacements remotely from radar satellite imagery by comparing its measurements to theoretical predictions. A previous validation study on a new bridge made of concrete deck on steel girders found a good match between satellite-measured thermal displacements and those from theoretical predictions. With the aim of validating the approach on various types of bridges, this publication presents the findings of additional validation studies on two historical bridges, each with a deck supported by a steel truss superstructure. Two sets of satellite imagery with different look angles were used to decompose the oblique measurements into vertical and longitudinal displacements for direct comparison with theoretical predictions. The results confirmed the validity of the approach and indicated which bridge features can be best accurately monitored by radar satellites.

The structural health of critical transport infrastructure, such as bridges, is difficult to assess and monitor. Existing methods of evaluation rely predominantly on visual inspection and/or the installation of sensors to measure the in-situ performance of structures. There are vast numbers of critical bridge structures that need to be monitored and these are often located in diverse geographical locations which are difficult and costly to access. Recent advances in satellite monitoring using Interferometric Synthetic Aperture Radar (InSAR) monitoring provide the opportunity for global coverage of assets and the measurement of displacement to sub-centimetre accuracy. Such technologies could provide bridge engineers and asset owners with insights about the health and behaviour of their assets. The key to successful implementation of InSAR monitoring of bridges lies in understanding the limitations and opportunities of InSAR, and making a clear case to satellite data providers on what specifications (resolution, frequency, processing assumptions) would unlock using such datasets for wider use in monitoring of infrastructure. This work examines the application of InSAR for bridge monitoring using case studies of several UK bridge structures. These bridge structures differ in structural form, material and environmental context, but each raise key considerations in practical application of InSAR, and the potential to spot unusual signs behaviour that would alert bridge owners to maintenance problems and potential failures.

Agriculture in the Central Valley, California, is made possible by surface water management infrastructure and the groundwater supply. However, groundwater overdraft leads to land subsidence, which in turn threatens flood control and water delivery infrastructure. Monitoring, modeling, and managing land subsidence are crucial to ensure the water supply and its infrastructure remains accessible for the future. Detection of land subsidence is difficult because it is a gradual deformation of the land surface over broad areas that can extend 10s of kilometers. Interferometric synthetic aperture radar (InSAR) is used to detect deformation over time using a series of repeat images that penetrate cloud cover. Satellite and airborne InSAR time series techniques identify and monitor the development of both valley-wide subsidence zones and individual, localized risks to infrastructure.

The state of urban land spatial structure, commonly referred to as urban form, for a given city reflects the cumulative impacts of past and present human activities. Conversely, the urban form influences urban activities, resources consumption and the environment. To improve understanding of the impacts of urban form and related urban issues, accurate description of urban land structure is a key information requirement, which include geospatial distributions of land use, surface characters and features derived from remote sensing imagery, as well as from integration and inference of supporting information from diverse sources. This paper presents the results of research on Canadian urban form including land use, land surface characterizations and changes, as well as the relationship of urban form with urban activities, urban commuting as an example, for improvement of understanding of the urban form and its impacts by using spatial information from image data at pixel level. The scope of this research is in a broad range in nature and includes information extraction from remote sensing image data, integration of land use time-series maps from diverse historic sources and finally spatial analysis and modeling of urban land structure impacts on intra-urban commute transportation. This paper presents an example of this data-information-knowledge processing.

There is an increase in the collection and availability of LiDAR data across Canada. While digital terrain and surface models are the most common derivative products, the LiDAR point cloud data can also be used to extract various layers of information, including vegetation, utility lines, bridges, and buildings. This paper describes the current initiative by the Canadian federal government to derive building footprints from LiDAR data in order to generate a building footprint dataset for Canada’s Open Data portal and to evaluate the minimum acceptable criteria for successful and accurate building extraction. The results provide guidelines for the minimum density requirements of LiDAR point cloud data for the extraction of building footprints in an urban setting. Two criteria were tested: (i) minimum point density and (ii) the effect of vendor-classified vs re-classified (classified using open-source tools) point data clouds in the building extraction process. Results indicate that vendor-classified point cloud data with a minimum density of 4 pts/m² is sufficient to accurately extract building footprints with >75% confidence. For re-classified LiDAR a density of at least 8 pts/m² would be required to meet this confidence level. However, commission errors found in the fully automatic re-classified method are numerous and manual editing or further algorithm refinements are necessary before it could be used in production.

Spring 2017 flooding in the Canadian provinces of Ontario and Quebec was caused by a number of consecutive record-setting rain events combined with melting snow from early April to mid-May. The event significantly damaged residential infrastructure by flooding approximately 2500 Quebec residences in 146 municipalities, forcing mass evacuations and declaration of a state of emergency. The International Charter on Space and Major Disasters was activated shortly after on May 6, providing near-real time earth observation data from a range of sensors through Charter member agencies. Upon activation, the Emergency Geomatics Services (EGS) at the Canada Centre for Mapping and Earth Observation (CCMEO), Natural Resources Canada (NRCan), produced flood maps from Canada’s RADARSAT-2 and Charter satellite imagery to provide up-to-date emergency situational awareness. Previous flood extraction methods that relied on manual thresholding of single bands were deemed suboptimal to map open water in a timely and efficient manner from all data received through the Charter. In addition, previous methods ignored flooding beneath vegetation, which produced a large underestimation of flood extents on vegetated floodplains. Work that was ongoing in the previous year to develop reliable surface water extraction methods from multiple sensors for floodplain characterization were quickly adapted and put into operations during the activation, enabling rapid flood map production from RADARSAT-2, Sentinel-1 and TerraSar-X, among other sensors. This chapter describes the methodology and presents successes, challenges and lessons learned from the 2017 EGS activation for flooding in Ontario and Quebec, Canada.

Landsat multispectral imagery has become a valuable resource for decision makers in environmental emergency response over the past three decades. In this chapter, Landsat-8 imagery was primarily utilized to assist spill investigations with three case studies: (1) wastewater spill due to a coal mine dam failure, (2) crude oil and saline produced water spill due to a pipeline leak, and (3) highly saline produced water spill due to a pipeline rupture. In case study 1, an early sign of seepage was detected from a containment pond 6 days prior to the dam failure using an automated endmember detection and abundance estimation method. In case study 2, an early sign of spill was detected more than a year before the spill was reported and time-series surface extent of the spill was quantified based on a simple difference of vegetation indices. In case study 3, spatial-temporal progression of highly saline spill was estimated using moisture indices and a spectral matching technique was used to verify the absence of spill on surface before it was reported. These case studies also utilized Sentinel-2 imagery for better understanding of post-spill remediation process and exemplify how publicly available spaceborne multispectral data might help establish the duration of spill event, reconstruct the spill scenario, and optimize the spill mitigation and prevention control planning.

The ongoing conflict in Syria has disastrously impacted the environment and public health. Fighting has destroyed cities with widespread damage to industrial sites and critical infrastructure. Analysis of the fighting, which is based on satellite imagery, social media monitoring, and the reports of International agencies, has identified that the cement industry has sustained severe damage; has been critical in the production of military works by all combatants, and will be critical in reconstruction. Quarries and cement factories have been seized by armed groups and fought over reducing or stopping production. In 2016, Turkey began closing the border with Syria completing 828 km of concrete wall by 2018. In the Afrin region, Kurdsh malitia built extensive networks of trenches, cut and cover hardened tunnels (CCHTs) and underground facilities (UGFs) using reinforced concrete to improve survivability. Airstrikes and artillery bombardment of urban areas throughout Syria have caused the destruction of a major part its housing stock. Millions of tonnes of conflict debris, some of which contains hazardous materials such as asbestos, heavy metals, and the toxic residues from weapons have been created. Cities will need to be reconstructed and to rebuild Aleppo city alone will require ca. 7.5 times the pre-war annual output of all the quarries in Syria. This will place an unprecedented demand on the quarrying and cement industry for concrete. The shortfall will require recycling and repurposing of conflict debris.