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Open AccessArticle

UAV Remote Sensing Surveillance of a Mine Tailings Impoundment in Sub-Arctic Conditions

1
Water Resources and Environmental Engineering, University of Oulu, P.O. Box 4300, FI-90014 Oulu, Finland
2
Norut Northern Research Institute, P.O. Box 6434, NO-9294 Tromsø, Norway
*
Author to whom correspondence should be addressed.
Remote Sens. 2017, 9(12), 1318; https://doi.org/10.3390/rs9121318
Received: 22 November 2017 / Revised: 12 December 2017 / Accepted: 12 December 2017 / Published: 15 December 2017
Mining typically involves extensive areas where environmental monitoring is spatially sporadic. New remote sensing techniques and platforms such as Structure from Motion (SfM) and unmanned aerial vehicles (UAVs) may offer one solution for more comprehensive and spatially continuous measurements. We conducted UAV campaigns in three consecutive summers (2015–2017) at a sub-Arctic mining site where production was temporarily suspended. The aim was to monitor a 0.5 km2 tailings impoundment and measure potential subsidence of tailings. SfM photogrammetry was used to produce yearly topographical models of the tailings surface, which allowed the amount of surface displacement between years to be tracked. Ground checkpoints surveyed in stable areas of the impoundment were utilized in assessing the vertical accuracy of the models. Observed surface displacements were linked to a combination of erosion, tailings settlement, and possible compaction of the peat layer underlying the tailings. The accuracy obtained indicated that UAV-assisted monitoring of tailings impoundments is sufficiently accurate for supporting impoundment management operations and for tracking surface displacements in the decimeter range. View Full-Text
Keywords: UAV; unmanned aerial vehicle; Structure from Motion; digital elevation model; DEM of difference; mine; tailings; ground displacement; settlement UAV; unmanned aerial vehicle; Structure from Motion; digital elevation model; DEM of difference; mine; tailings; ground displacement; settlement
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MDPI and ACS Style

Rauhala, A.; Tuomela, A.; Davids, C.; Rossi, P.M. UAV Remote Sensing Surveillance of a Mine Tailings Impoundment in Sub-Arctic Conditions. Remote Sens. 2017, 9, 1318.

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