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Application of Sentinel-1 InSAR to monitor tailings dams and predict geotechnical instability: practical considerations based on case study insights.
- Source :
-
Bulletin of Engineering Geology & the Environment . May2024, Vol. 83 Issue 5, p1-25. 25p. - Publication Year :
- 2024
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Abstract
- Tailings storage facilities (TSFs) impound mining waste behind dams to ensure public safety, but failure incidents have prompted calls for more robust monitoring programs. Satellite-based interferometric synthetic aperture radar (InSAR) has grown in popularity due to its ability to remotely detect millimeter-scale displacements in most urban and some natural terrains. However, there remains a limited understanding of whether InSAR can be as accurate or representative as on-the-ground instruments, whether failures can be predicted in advance using InSAR, and what variables govern the quality and reliability of InSAR results. To address these gaps, we analyze open-source, medium-resolution Sentinel-1 data to undertake a ground-truth assessment at a test site and a forensic analysis of five failure cases. We use a commercial software with an automated Persistent Scatterer (PS) workflow (SARScape Analytics) for all case study sites except one and a proprietary algorithm (SqueeSAR) with a dual PS and Distributed Scatterer (DS) algorithm for the ground-truth site and one forensic case. The main goal is to deliver practical insights regarding the influence of algorithm/satellite selection, environmental conditions, site activity, coherence thresholds, satellite-dam geometry, and failure modes. We conclude that Sentinel-1 InSAR can serve as a hazard-screening tool to help guide where to undertake targeted investigations; however, most potential failure modes may not exhibit InSAR-detectable accelerations that could assist with time-of-failure prediction in real time. As such, long-term monitoring programs should ideally be integrated with a combination of remote sensing and field instrumentation to best support engineering practice and judgment. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14359529
- Volume :
- 83
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- Bulletin of Engineering Geology & the Environment
- Publication Type :
- Academic Journal
- Accession number :
- 176964581
- Full Text :
- https://doi.org/10.1007/s10064-024-03680-3