From Satellites to Safety: An Open-Source SBAS Workflow for Ground Deformation Monitoring.
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| Title: | From Satellites to Safety: An Open-Source SBAS Workflow for Ground Deformation Monitoring. |
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| Authors: | Molada-Tebar, Adolfo1 (AUTHOR), Nuño-Villanueva, Natalia1 (AUTHOR), Morcillo-Sanz, Alberto1 (AUTHOR), González-Aguilera, Diego1 (AUTHOR) daguilera@usal.es |
| Source: | Remote Sensing. Jun2026, Vol. 18 Issue 11, p1863. 31p. |
| Subjects: | Radar interferometry, Mine safety, Open source software, Interferometry, Software libraries (Computer programming) |
| Geographic Terms: | Sweden |
| Abstract: | Highlights: What are the main findings? A robust and semi-automated Small Baseline Subset (SBAS) workflow using the open source hyp3_sbas Python library has been implemented for large-scale ground deformation monitoring in mining environments. The workflow efficiently detects millimetric-scale deformation patterns at the Björkdal gold mine using Sentinel-1 data. What are the implications of the main findings? The use of the hyp3_sbas Python implementation reduces the learning curve of the complex SBAS methodology, enabling non-expert users to perform analyses. The proposed Interferometric Synthetic Aperture Radar (InSAR) workflow provides reproducible, scalable, and operationally ready satellite-based monitoring of mining infrastructure, facilitating the integration of InSAR techniques into risk prevention strategies and supporting sustainable mining management. Ground deformation monitoring is critical for safety and environmental management in modern mining. Active mining sites are highly exposed to terrain instabilities and subsidence, risking infrastructure integrity, disrupting operations, and posing hazards to communities. In this context, Differential Synthetic Aperture Radar Interferometry (DInSAR) techniques provide an effective and non-invasive tool capable of detecting millimetric surface displacements. This study implements the Small Baseline Subset (SBAS) technique through an open-source workflow based on the Python package hyp3_sbas, enabling semi-automated and reproducible interferometric processing by combining HyP3 with MintPy. The workflow is applied to the Björkdal gold mine (Sweden), a pilot site of the Horizon Europe XTRACT project focused on enhancing resilience in critical raw material supply chains. Integrating Sentinel-1 viewing geometries resolves the true vertical deformation field, yielding an overall mean velocity of −3.99 mm/year across the mining complex, with significant displacement rates concentrated below the 25th percentile (Q1) at −11.07 mm/year. Sector-specific analysis reveals localised subsidence accelerating over underground footprints and tailings storage facilities (mean velocities of −6.56 and −3.98 mm/year; Q1 thresholds near −13.00 mm/year), contrasting with the geomechanical stability observed at the open-pit area (mean: −0.45 mm/year). The proposed open-source framework shows strong potential for operational satellite-based monitoring, supporting predictive maintenance and early-warning strategies for risk management in mining environments while simplifying and standardising the interferometric processing workflow. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Highlights: What are the main findings? A robust and semi-automated Small Baseline Subset (SBAS) workflow using the open source hyp3_sbas Python library has been implemented for large-scale ground deformation monitoring in mining environments. The workflow efficiently detects millimetric-scale deformation patterns at the Björkdal gold mine using Sentinel-1 data. What are the implications of the main findings? The use of the hyp3_sbas Python implementation reduces the learning curve of the complex SBAS methodology, enabling non-expert users to perform analyses. The proposed Interferometric Synthetic Aperture Radar (InSAR) workflow provides reproducible, scalable, and operationally ready satellite-based monitoring of mining infrastructure, facilitating the integration of InSAR techniques into risk prevention strategies and supporting sustainable mining management. Ground deformation monitoring is critical for safety and environmental management in modern mining. Active mining sites are highly exposed to terrain instabilities and subsidence, risking infrastructure integrity, disrupting operations, and posing hazards to communities. In this context, Differential Synthetic Aperture Radar Interferometry (DInSAR) techniques provide an effective and non-invasive tool capable of detecting millimetric surface displacements. This study implements the Small Baseline Subset (SBAS) technique through an open-source workflow based on the Python package hyp3_sbas, enabling semi-automated and reproducible interferometric processing by combining HyP3 with MintPy. The workflow is applied to the Björkdal gold mine (Sweden), a pilot site of the Horizon Europe XTRACT project focused on enhancing resilience in critical raw material supply chains. Integrating Sentinel-1 viewing geometries resolves the true vertical deformation field, yielding an overall mean velocity of −3.99 mm/year across the mining complex, with significant displacement rates concentrated below the 25th percentile (Q1) at −11.07 mm/year. Sector-specific analysis reveals localised subsidence accelerating over underground footprints and tailings storage facilities (mean velocities of −6.56 and −3.98 mm/year; Q1 thresholds near −13.00 mm/year), contrasting with the geomechanical stability observed at the open-pit area (mean: −0.45 mm/year). The proposed open-source framework shows strong potential for operational satellite-based monitoring, supporting predictive maintenance and early-warning strategies for risk management in mining environments while simplifying and standardising the interferometric processing workflow. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 20724292 |
| DOI: | 10.3390/rs18111863 |
