QUANTIFYING UNCERTAINTY IN INSAR-DERIVED DISPLACEMENT MEASUREMENTS FOR BRIDGE MONITORING
Liuzzo, Riccardo ; Giordano, Pier Francesco and Limongelli, Maria Pina LU
(2025)
Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2025
- Abstract
Bridge monitoring is essential for ensuring their long-term safety, reducing disruptions, and supporting economic and social activities. Traditional monitoring techniques rely on periodic inspections and contact-based sensing systems, which, while effective, have limitations due especially to high installation and maintenance costs. Satellite-based Synthetic Aperture Radar Interferometry (InSAR) offers a complementary, non-intrusive solution for Structural Health Monitoring, providing displacement time histories with millimetric precision through velocity maps. However, InSAR data from different orbits are typically acquired at different times and with non-homogeneous spatial distributions of measuring points. Therefore, when combining... (More)
Bridge monitoring is essential for ensuring their long-term safety, reducing disruptions, and supporting economic and social activities. Traditional monitoring techniques rely on periodic inspections and contact-based sensing systems, which, while effective, have limitations due especially to high installation and maintenance costs. Satellite-based Synthetic Aperture Radar Interferometry (InSAR) offers a complementary, non-intrusive solution for Structural Health Monitoring, providing displacement time histories with millimetric precision through velocity maps. However, InSAR data from different orbits are typically acquired at different times and with non-homogeneous spatial distributions of measuring points. Therefore, when combining InSAR measurements from ascending and descending satellite orbits, spatial and temporal resampling processes are necessary, which introduce uncertainty in the reconstructed structural displacements. This paper applies a recently developed method to quantify the uncertainty introduced by resampling processes, focusing on grid spatial subsampling and linear temporal interpolation. Using displacement data from the European Ground Motion Service (EGMS), we investigate the behavior of the Schottwien Viaduct, a major prestressed concrete bridge in Austria. By employing error propagation theory, we assess how InSAR data processing impacts the precision of InSAR-derived displacement estimates. The analysis provides insights into uncertainty quantification, which informs the selection of the most suitable EGMS dataset and guides the optimization of grid configurations for structural displacement reconstruction. The findings contribute to improving the reliability of satellite-based SHM and highlight key considerations for integrating InSAR data into large-scale infrastructure monitoring.
(Less)
- author
- Liuzzo, Riccardo
; Giordano, Pier Francesco
and Limongelli, Maria Pina
LU
- organization
- publishing date
- 2025
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- bridge, displacement, EGMS, InSAR, remote sensing, Sentinel 1, Structural Health Monitoring, transportation infrastructures
- host publication
- Proceedings of SPIE . The International Society for Optical Engineering
- editor
- Limongelli, Maria Pina ; Ng, Ching Tai and Ozevin, Didem
- article number
- 134350F
- publisher
- SPIE
- conference name
- Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2025
- conference location
- Vancouver, Canada
- conference dates
- 2025-03-17 - 2025-03-20
- external identifiers
-
- scopus:105014503942
- ISBN
- 9781510686564
- DOI
- 10.1117/12.3050715
- language
- English
- LU publication?
- yes
- id
- 2f5eb640-a003-48c3-95a1-ff4713eea60b
- date added to LUP
- 2025-11-17 11:06:30
- date last changed
- 2025-11-17 11:07:26
@inproceedings{2f5eb640-a003-48c3-95a1-ff4713eea60b,
abstract = {{<p>Bridge monitoring is essential for ensuring their long-term safety, reducing disruptions, and supporting economic and social activities. Traditional monitoring techniques rely on periodic inspections and contact-based sensing systems, which, while effective, have limitations due especially to high installation and maintenance costs. Satellite-based Synthetic Aperture Radar Interferometry (InSAR) offers a complementary, non-intrusive solution for Structural Health Monitoring, providing displacement time histories with millimetric precision through velocity maps. However, InSAR data from different orbits are typically acquired at different times and with non-homogeneous spatial distributions of measuring points. Therefore, when combining InSAR measurements from ascending and descending satellite orbits, spatial and temporal resampling processes are necessary, which introduce uncertainty in the reconstructed structural displacements. This paper applies a recently developed method to quantify the uncertainty introduced by resampling processes, focusing on grid spatial subsampling and linear temporal interpolation. Using displacement data from the European Ground Motion Service (EGMS), we investigate the behavior of the Schottwien Viaduct, a major prestressed concrete bridge in Austria. By employing error propagation theory, we assess how InSAR data processing impacts the precision of InSAR-derived displacement estimates. The analysis provides insights into uncertainty quantification, which informs the selection of the most suitable EGMS dataset and guides the optimization of grid configurations for structural displacement reconstruction. The findings contribute to improving the reliability of satellite-based SHM and highlight key considerations for integrating InSAR data into large-scale infrastructure monitoring.</p>}},
author = {{Liuzzo, Riccardo and Giordano, Pier Francesco and Limongelli, Maria Pina}},
booktitle = {{Proceedings of SPIE . The International Society for Optical Engineering}},
editor = {{Limongelli, Maria Pina and Ng, Ching Tai and Ozevin, Didem}},
isbn = {{9781510686564}},
keywords = {{bridge; displacement; EGMS; InSAR; remote sensing; Sentinel 1; Structural Health Monitoring; transportation infrastructures}},
language = {{eng}},
publisher = {{SPIE}},
title = {{QUANTIFYING UNCERTAINTY IN INSAR-DERIVED DISPLACEMENT MEASUREMENTS FOR BRIDGE MONITORING}},
url = {{http://dx.doi.org/10.1117/12.3050715}},
doi = {{10.1117/12.3050715}},
year = {{2025}},
}