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Article

Virtual Structural Analysis of Jokisivu Open Pit Using ‘Structure-from-Motion’ Unmanned Aerial Vehicles (UAV) Photogrammetry: Implications for Structurally-Controlled Gold Deposits in Southwest Finland

1
Geological Survey of Finland, P.O. Box 96, FI-02151 Espoo, Finland
2
Departmento de Geodinámica, Universidad de Granada, 18002 Granada, Spain
3
Dragon Mining, Uudenniityntie 224, FI-32700 Huittinen, Finland
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(8), 1296; https://doi.org/10.3390/rs10081296
Submission received: 19 June 2018 / Revised: 6 August 2018 / Accepted: 11 August 2018 / Published: 16 August 2018

Abstract

Unmanned aerial vehicles (UAVs) are rapidly growing remote sensing platforms for capturing high-resolution images of exposed rock surfaces. We used a DJI Phantom 3 Professional (P3P) quadcopter to capture aerial images that were used to generate a high-resolution three-dimensional (3-D) model of the Jokisivu open-pit gold deposit that is located in southwestern Finland. 158 overlapping oblique and nadir images were taken and processed with Agisoft Photoscan Pro to generate textured 3-D surface models. In addition, 69 overlapping images were taken from the steep faces of the open pit. We assessed the precision of the 3-D model by deploying ground control points (GCPs) and the average errors were found minimal along X (2.0 cm), Y (1.2 cm), and Z (5.0 cm) axes. The steep faces of the open pit were used for virtual structural measurements and kinematic analyses in CloudCompare and ArcGIS to distinguish the orientation of different fracture sets and statistical categorization, respectively. Three distinct fracture sets were observed. The NW-SE and NE-SW striking fractures form a conjugate geometry, whereas the NNW-SSE striking fractures cut the conjugate fracture set. The orientation of conjugate fractures match well with the resource model of the deposit and NW- and NE-trending segments of regional-scale anastomosing shear zones. Based on the conjugate geometry of fracture sets I and II, and the regional pattern of anastomosing shear system lead us to interpret an origin of gold mineralization in two stages. An early N-S or NNW-SSE crustal shortening, corresponding to the regional D4 (ca. 1.83–1.81 Ga) or pre-D4 (ca. 1.87–1.86 Ga) Svecofennian tectonic event(s) that produced anastomosing shear zones. Subsequent E-W directed D5 contraction (ca. 1.79–1.77 Ga) partly reactivated the anastomosing shear zones with the formation of conjugate system, which controlled the migration of fluids and gold mineralization in SW Finland.
Keywords: UAV; open-pit mine; gold deposit; structure-from-motion; shear fractures UAV; open-pit mine; gold deposit; structure-from-motion; shear fractures
Graphical Abstract

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MDPI and ACS Style

Sayab, M.; Aerden, D.; Paananen, M.; Saarela, P. Virtual Structural Analysis of Jokisivu Open Pit Using ‘Structure-from-Motion’ Unmanned Aerial Vehicles (UAV) Photogrammetry: Implications for Structurally-Controlled Gold Deposits in Southwest Finland. Remote Sens. 2018, 10, 1296. https://doi.org/10.3390/rs10081296

AMA Style

Sayab M, Aerden D, Paananen M, Saarela P. Virtual Structural Analysis of Jokisivu Open Pit Using ‘Structure-from-Motion’ Unmanned Aerial Vehicles (UAV) Photogrammetry: Implications for Structurally-Controlled Gold Deposits in Southwest Finland. Remote Sensing. 2018; 10(8):1296. https://doi.org/10.3390/rs10081296

Chicago/Turabian Style

Sayab, Mohammad, Domingo Aerden, Markku Paananen, and Petri Saarela. 2018. "Virtual Structural Analysis of Jokisivu Open Pit Using ‘Structure-from-Motion’ Unmanned Aerial Vehicles (UAV) Photogrammetry: Implications for Structurally-Controlled Gold Deposits in Southwest Finland" Remote Sensing 10, no. 8: 1296. https://doi.org/10.3390/rs10081296

APA Style

Sayab, M., Aerden, D., Paananen, M., & Saarela, P. (2018). Virtual Structural Analysis of Jokisivu Open Pit Using ‘Structure-from-Motion’ Unmanned Aerial Vehicles (UAV) Photogrammetry: Implications for Structurally-Controlled Gold Deposits in Southwest Finland. Remote Sensing, 10(8), 1296. https://doi.org/10.3390/rs10081296

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