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RSS FeedsRemote Sensing, Vol. 10, Pages 1507: Monitoring the Vulnerability of the Dam and Dikes in Germano Iron Mining Area after the Collapse of the Tailings Dam of Fundão (Mariana-MG, Brazil) Using DInSAR Techniques with TerraSAR-X Data (Remote Sensing)

 
 

24 september 2018 22:01:11

 
Remote Sensing, Vol. 10, Pages 1507: Monitoring the Vulnerability of the Dam and Dikes in Germano Iron Mining Area after the Collapse of the Tailings Dam of Fundão (Mariana-MG, Brazil) Using DInSAR Techniques with TerraSAR-X Data (Remote Sensing)
 


The Fundão tailings dam in the Germano iron mining complex (Mariana, Brazil) collapsed on the afternoon of 5 November 2015, and around 32.6 million cubic meters of mining waste spilled from the dam, causing polluion with mining waste along a trajectory of 668 km, extending to the Atlantic Ocean. The Sela & Tulipa and Selinha dikes, and the main Germano tailings dam, were directly or indirectly affected by the accident. This work presents an investigation using Advanced-Differential Interferometric Synthetic Aperture Radar (A-DInSAR) techniques for risk assessment in these critical structures during 18 months after the catastrophic event. The approach was based on the integration of SBAS (Small Baseline Subset) and PSI (Persistent Scatterer Interferometry) techniques, aiming at detecting linear and nonlinear ground displacements in these mining structures. It used a set of 48 TerraSAR-X images acquired on ascending mode from 11 November 2015 to 15 May 2017. The results provided by the A-DInSAR analysis indicated an overall stability in the dikes and in the main wall of Germano tailings dam, which is in agreement with in situ topographic monitoring. In addition, it was possible to detect areas within the reservoir showing accumulated values of up to −125 mm of subsidence, probably caused by settlements of the waste dry material due to the interruption of the mining waste deposition, and values up to −80 mm on auxiliary dikes, probably caused by continuous traffic of heavy equipment. The spatiotemporal information of surface displacement of this large mining structure can be used for future operational planning and risk control.


 
43 viewsCategory: Geology, Physics
 
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