PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
June 29, 2024e-Journal of Nondestructive Testing0 citationsOpen Access

Utilising InSAR for monitoring infrastructure at national scales

View Full Paper
NMNathan MagnallTITom InglebySDSarah N. Douglas

Key Points

Key points are not available for this paper at this time.

Abstract

Interferometric SAR (InSAR) is now a widely used tool for the monitoring of infrastructure, in particular mines, dams, and oil and gas facilities. The technology is also widely used for the monitoring of construction activities such as tunnelling. With the growth of globally available and continuously updated SAR datasets, the monitoring of entire regional and national infrastructure networks is now feasible. Here we show how continuously updated, network-wide, InSAR datasets can be used to proactively manage large infrastructure networks such as roads, railways, and water pipelines. In the UK continuously updated InSAR data (derived from Sentinel-1 SAR data) is being effectively used across the entire railway network to proactively monitor potential embankment failures, large-scale landslides, and potential hazards outside of the boundary fence. A challenge of using InSAR data in this way is the huge volume of data that is available, as such custom risk metrics and machine learning algorithms are applied to highlight some of the areas at heightened risk. InSAR is also being applied to tackle the issue of water pipe leakage caused by natural ground movements, such as soil shrink-swell. In this case, regularly updated InSAR data has been used in the UK and Australia to detect areas at elevated risk of pipeline failures based on ground movement patterns, and by combining historical movement data and known failure events it is possible to refine such models. With expanding global SAR constellations proactive, nationwide, monitoring of critical assets is now possible, with the challenge being how we derive insight from these very large datasets.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Magnall et al. (2024) studied this question.

synapsesocial.com/papers/68e629b8b6db6435875bcd36https://doi.org/10.58286/29645
Ask AI
Helpful
Bookmark
Share
View Full Paper

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Phase unwrapping for large SAR interferograms: statistical segmentation and generalized network models2002 · 850 citations
  2. 2Comparison of in situ and interferometric synthetic aperture radar monitoring to assess bridge thermal expansion2022 · 14 citations
  3. 3A new method for measuring deformation on volcanoes and other natural terrains using InSAR persistent scatterers2004 · 1,822 citations
  4. 4A multi‐temporal InSAR method incorporating both persistent scatterer and small baseline approaches2008 · 1,259 citations
  5. 5InSAR processing for volcano monitoring and other near‐real time applications2016 · 101 citations