A Data-Driven InSAR Failure-Risk Index for Early Warning of Mining Infrastructure Instability: The Çöpler Case Study, İliç, Türkiye.
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| Title: | A Data-Driven InSAR Failure-Risk Index for Early Warning of Mining Infrastructure Instability: The Çöpler Case Study, İliç, Türkiye. |
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| Authors: | Cavur, Mahmut1 (AUTHOR) |
| Source: | Remote Sensing. Aug2026, Vol. 18 Issue 15, p2624. 30p. |
| Subjects: | Deformations (Mechanics), Radar interferometry, Mines & mineral resources, Strip mining, Risk managers |
| Geographic Terms: | Türkiye, Erzincan (Türkiye) |
| Abstract: | Highlights: What are the main findings? A novel InSAR-based Failure-Risk Index (FRI) integrates displacement, velocity, and especially deformation acceleration into a single standardized early-warning metric for mining infrastructure. Deformation acceleration exhibited a statistically significant regime change beginning in 2020—approximately four years prior to the February 2024 Çöpler Mine collapse—providing a substantially earlier warning than velocity-based methods. What is the implication of the main finding? Acceleration-based monitoring enables statistically significant change-point detection, transforming Interferometric Synthetic Aperture Radar (InSAR) from a descriptive monitoring tool into a proactive early warning system for open-pit mines and tailing dams. The transferable 0–2 FRI classification framework supports risk-based decision-making, emergency protocol activation, and improved operational safety in large scale mining environments. Failures at large-scale open-pit mines and tailing dams pose critical risks to human life, environmental systems, and economic sustainability. Although Interferometric Synthetic Aperture Radar (InSAR) has proven effective in detecting long-term surface deformation, a scientifically robust early-warning framework has not yet been established because standardized quantitative thresholds that are capable of distinguishing benign consolidation settlement from instability-driven deformation remain unavailable.InSAR has proven effective for detecting long-term surface deformation. However, a scientific early-warning framework has not yet been proposed or developed due to the absence of standardized quantitative thresholds that distinguish benign consolidation settlement from instability-driven deformation. This research proposes a novel InSAR-based Failure-Risk Index (FRI) that integrates displacement, velocity, and, most importantly, deformation acceleration into a single, normalized metric as an early warning system for mining infrastructure instability. The framework that we propose (i) emphasizes acceleration as a leading indicator of change in mechanical regime, (ii) incorporates a statistically guided separation of long-term consolidation settlement from anomalous deformation based on baseline variability, (iii) applies a statistical standardization and change-point detection system. The methodology is validated through a retrospective analysis of the heap leach failure—that occurred in Çöpler Gold Mine in Erzincan, Türkiye, on 13 February 2024—by using a set of Sentinel-1 time-series images collected between 2014 and 2024. The results prove that while displacement and velocity remained within ranges typically interpreted as stable, deformation acceleration exhibited a statistically significant increase that began around 2020, exceeded baseline variability by approximately two orders of magnitude, which is approximately four years before the collapse, and marked the onset of tertiary creep and progressive instability. The proposed FRI framework successfully captures this transition and provides a transferable, meaningful early-warning framework to support proactive risk management and improve the safety of mining infrastructure. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 196272304 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Data-Driven InSAR Failure-Risk Index for Early Warning of Mining Infrastructure Instability: The Çöpler Case Study, İliç, Türkiye. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Cavur%2C+Mahmut%22">Cavur, Mahmut</searchLink><relatesTo>1</relatesTo> (AUTHOR) – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Aug2026, Vol. 18 Issue 15, p2624. 30p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Deformations+%28Mechanics%29%22">Deformations (Mechanics)</searchLink><br /><searchLink fieldCode="DE" term="%22Radar+interferometry%22">Radar interferometry</searchLink><br /><searchLink fieldCode="DE" term="%22Mines+%26+mineral+resources%22">Mines & mineral resources</searchLink><br /><searchLink fieldCode="DE" term="%22Strip+mining%22">Strip mining</searchLink><br /><searchLink fieldCode="DE" term="%22Risk+managers%22">Risk managers</searchLink> – Name: SubjectGeographic Label: Geographic Terms Group: Su Data: <searchLink fieldCode="DE" term="%22Türkiye%22">Türkiye</searchLink><br /><searchLink fieldCode="DE" term="%22Erzincan+%28Türkiye%29%22">Erzincan (Türkiye)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? A novel InSAR-based Failure-Risk Index (FRI) integrates displacement, velocity, and especially deformation acceleration into a single standardized early-warning metric for mining infrastructure. Deformation acceleration exhibited a statistically significant regime change beginning in 2020—approximately four years prior to the February 2024 Çöpler Mine collapse—providing a substantially earlier warning than velocity-based methods. What is the implication of the main finding? Acceleration-based monitoring enables statistically significant change-point detection, transforming Interferometric Synthetic Aperture Radar (InSAR) from a descriptive monitoring tool into a proactive early warning system for open-pit mines and tailing dams. The transferable 0–2 FRI classification framework supports risk-based decision-making, emergency protocol activation, and improved operational safety in large scale mining environments. Failures at large-scale open-pit mines and tailing dams pose critical risks to human life, environmental systems, and economic sustainability. Although Interferometric Synthetic Aperture Radar (InSAR) has proven effective in detecting long-term surface deformation, a scientifically robust early-warning framework has not yet been established because standardized quantitative thresholds that are capable of distinguishing benign consolidation settlement from instability-driven deformation remain unavailable.InSAR has proven effective for detecting long-term surface deformation. However, a scientific early-warning framework has not yet been proposed or developed due to the absence of standardized quantitative thresholds that distinguish benign consolidation settlement from instability-driven deformation. This research proposes a novel InSAR-based Failure-Risk Index (FRI) that integrates displacement, velocity, and, most importantly, deformation acceleration into a single, normalized metric as an early warning system for mining infrastructure instability. The framework that we propose (i) emphasizes acceleration as a leading indicator of change in mechanical regime, (ii) incorporates a statistically guided separation of long-term consolidation settlement from anomalous deformation based on baseline variability, (iii) applies a statistical standardization and change-point detection system. The methodology is validated through a retrospective analysis of the heap leach failure—that occurred in Çöpler Gold Mine in Erzincan, Türkiye, on 13 February 2024—by using a set of Sentinel-1 time-series images collected between 2014 and 2024. The results prove that while displacement and velocity remained within ranges typically interpreted as stable, deformation acceleration exhibited a statistically significant increase that began around 2020, exceeded baseline variability by approximately two orders of magnitude, which is approximately four years before the collapse, and marked the onset of tertiary creep and progressive instability. The proposed FRI framework successfully captures this transition and provides a transferable, meaningful early-warning framework to support proactive risk management and improve the safety of mining infrastructure. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs18152624 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 30 StartPage: 2624 Subjects: – SubjectFull: Deformations (Mechanics) Type: general – SubjectFull: Radar interferometry Type: general – SubjectFull: Mines & mineral resources Type: general – SubjectFull: Strip mining Type: general – SubjectFull: Risk managers Type: general – SubjectFull: Türkiye Type: general – SubjectFull: Erzincan (Türkiye) Type: general Titles: – TitleFull: A Data-Driven InSAR Failure-Risk Index for Early Warning of Mining Infrastructure Instability: The Çöpler Case Study, İliç, Türkiye. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Cavur, Mahmut IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 08 Text: Aug2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 18 – Type: issue Value: 15 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
