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Private: 5 things every risk manager and surveyor should know about ground displacement mapping with InSAR

August 19, 2021
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Earth Data, Simplified

No matter the scale, complexity, or importance of a project, ground displacement continues to be a real and credible ongoing threat requiring continuous monitoring.  

Traditional, tried-and-tested methods remain important, but technology is not only catching up it is now advancing at pace offering new ways to boost the way we build, maintain, and protect our projects.  

One of those ways is InSAR – a satellite-based surveying capability which has evolved from the academic realm in the 1990s to operational application for well over 20 years. InSAR based land displacement monitoring offers an affordable, efficient, and powerful addition to any risk management strategy.  

To explain more, we asked our product marketing manager, Shawn Melamed, to share his top five things you need to know about using InSAR and how it can transform the way you and your company manage risk. 

1. Measuring Ground Displacement is an important piece of your risk mitigation approach

Ground displacement can be a hazard and a precursor to potential damage and failures of slopes, equipment, buildings, and infrastructure.  

By detecting subtle movement of the ground near sensitive equipment and structures, it is possible to prevent serious damage and catastrophic failures of critical assets, such as pipelines, rail, dams, and bridges. If we zoom in on dams, we can understand the importance of constant monitoring for these subtle warning signs. This is because a single failure can cause billions of dollars in economic, environmental, and personal loss, such as Brazil’s Brumadinho dam disaster of 2019 and China’s recent double dam failure on July 18, 2021. Furthermore, the Association of State Dam Safety Organization (ASDSO) released a study that found that 30% of all dam failures are caused by foundational defects, including settlement and slope instability. 

Ground displacement measurements can provide early warning signs of potential operational issues. For example, clay rich soils, which are distributed across much of the UK and Europe are prone to a phenomenon known as shrink-swell, which causes uplift and subsidence due to varying moisture levels in the soil. This issue is expected to become much worse in the coming decades due to extreme weather caused by climate change and is projected to cause billions of dollars’ worth of damage to buildings and infrastructure.  

 This interactive map, published by the UNESCO Land Subsidence International Initiative classifies how the degree to which subsidence is a critical issue globally. 

2. Selecting the best data and algorithm for your application and area is critical

Many satellite data sources and InSAR algorithms are available, thus selecting the correct approach for a given application is critical to providing good quality results.  

Factors including the size of the feature being monitored, how often new measurements are required, the presence of certain landcover and terrain all must be taken into consideration.  

Common Algorithms:

  1. Differential SAR Interferometry (DInSAR) – Suitable for analyzing natural hazards – such as volcanoes, earthquakes and landslides – it works by comparing the signal phase change between two SAR images captured over the same area. While it may not be ideal for precision monitoring, it is useful to analyze general trends over large areas, such as cities, counties, states, and nations. 
  2. Persistent Scatterer Interferometry (PSI) – Sometimes known as Permanent Scatterer Interferometry, PSI is a state-of-the-art technique using a stack of SAR images captured over the same area to measure ground displacement from stable reflectors. It’s a more precise and reliable method and is ideal for monitoring infrastructure and individual structures. However, it requires a dense stack of 15-20 images and may result in limited measurements in areas with unsuitable landcover (forests, agriculture, water bodies, steep slopes). 
  3. Short-baseline Subset (SBAS) – A technique used to improve the number of valid measurements within a stack by computing interferograms for all image pair combinations within a specific date range and acquisition location.  
  4. SBAS-PSI – is a hybrid model which leverages the benefits from both algorithms. The PSI algorithm ensures only reliable measurements from stable points are measured and SBAS helps to ensure a denser delivery of measurements 

Common Data Sources:

  1. Medium Resolution (MR) – Ideal for studying natural hazards, it’s an important component in the cost-effective tip and cue (see No.3) monitoring model thanks to the large footprints and readily accessible imagery. Most commercial sensors offer MR data within their product portfolios. MR is also available through the widely used Sentinel-1 open-source data  
  2. Very High Resolution (VHR) – Designed for precision monitoring of individual segments of infrastructure, construction projects, and on individual buildings, there are many commercial platforms that offer this type of data includingRADARSAT-2, TerraSAR-X, ALOS COSMO-Skymed, to name a few. All these sensors can acquire InSAR suitable sub-meter resolution data. Furthermore, there are many new small sat constellations being launched and commissioned for InSAR applications including Capella Space and ICEYE. It will not be long until there are hundreds of new SAR sensors capable of capturing same day measurements. Many consider this to be the Golden Age of SAR imagery. 

3. Get the best of both worlds with open-source and commercial SAR data with tip and cue

Tip and cue is a powerful technique using readily accessible medium-resolution (MR) SAR imagery and very high resolution (VHR) SAR imagery. By combining the two you get the best of both worlds – cost-effective large area monitoring and precision monitoring of individual assets.  

 The concept is simple: low-cost MR imagery monitors larger areas for general trends to identify regions of potential risk. Very high resolution (VHR) imagery is then procured over smaller areas if potential risk is identified. A more detailed inspection of the asset can then be performed to further refine additional monitoring requirements. 

4. Satellite InSAR compliments traditional ground surveying

While conventional ground-based instruments (such as GPS, ground leveling, etc.) provide continuous monitoring with high accuracy, their high costs limits the spatial coverage that can be achieved economically. InSAR collects dense networks of measurements over large areas to provide additional information where ground measurements are not available, offering more protection and reducing the reliance on expensive in situ measurements and manual surveying.

Combining conventional surveying with InSAR offers the following benefits:

  • Measurement validation – A subset of the in-situ measurements can be used to validate the InSAR measurements 
  • Important calibration – A subset of the in-situ measurements can be used to calibrate the InSAR measurements to further improve their accuracy 
  • Manual Surveying – Can be used to capture measurements in areas where InSAR cannot, such as under dense canopy 
  • Fixed GNSS stations for sensitive areas – Fixed GPS/GNSS stations are still ideal for very sensitive areas due to their real-time continuous measurements 

5. InSAR is a proven technique that was developed over many decades

The science behind InSAR has been developed and validated over the last several decades. It was first introduced in the 1980s and was heavily developed throughout the 90s with the launch of SAR satellites like RADARSAT-1, ERS-1/2 and JERS-1. As sources of good quality SAR data increased, so did the operational adoption by many different engineering organizations. 

Early applications were mostly focused on monitoring natural hazards including volcanos, earthquakes, and landslides. Over time more SAR satellited has become increasingly become ubiquitous thanks to many new launches as well as vast improvements in data distribution via cloud-based architectures. Hundreds of new very high resolution (VHR) SAR satellites capable of capturing sub-daily measurements will soon become a reality, which provides for many opportunities to increase the temporal and spatial frequency of satellite based InSAR measurements.  

 By combining these multiple sources of SAR data with advanced algorithms, information extraction from these complex systems can be greatly simplified. At CATALYST, we are committed to simplifying access to our science and broadening the use of earth observation technology.