1,363
Views
11
CrossRef citations to date
0
Altmetric
Research Article

On the application of drones: a progress report in mining operations

, , , , , ORCID Icon, & show all
Pages 235-267 | Received 29 May 2020, Accepted 29 Jul 2020, Published online: 13 Aug 2020

References

  • S.L. Jämsä-Jounela, Future trends in process automation, Finland, annual reviews in control. 31 (2007), pp. 211–220.
  • S. Javad, E. Talebi, P. Roghanchi, and M. Hassanalian, A comprehensive review of applications of drone technology in the mining industry, (2020), doi: 10.3390/drones4030034.
  • M. Hassanalian and A. Abdelkefi, Classifications, applications, and design challenges of drones: A review, Prog. Aerosp. Sci. 91 (2017), pp. 99–131. doi:10.1016/j.paerosci.2017.04.003.
  • L.R. Newcome, Unmanned aviation: a brief history of unmanned aerial vehicles, 2004.
  • B. Holman, The first air bomb: Venice, 15 July 1849, Airminded. Airpower and British society, 2009.
  • U. Hannerz, Media and the world as a single place, in foreign news: exploring the world of foreign correspondents, 2000.
  • J.G. Leishman and B. Johnson, Engineering analysis of the 1907 cornu helicopter, J. Am. Helicopter Soc (2009). doi:10.4050/jahs.54.034001.
  • A.D. Harvey, Floatplanes, Flying Boats and Oceanic Warfare, 1939-1945, Air Power Hist. 57 (2010), pp. 4–19.
  • R.R.L. Constantine and J. Rey, Eyes in the sky: a review of civilian unmanned aerial vehicles (UAVs), Int. J. Comput. Appl 173:6 (2017), pp. 36–41.
  • R.P.G. Collinson and R.P.G. Collinson, Unmanned air vehicles, introduction to avionics systems, (2011).
  • A.J. Slack, Sources: military robots and drones: a reference handbook, Ref. User Serv. Q. (2013) doi: 10.5860/rusq.53n1.88b.
  • A.M.R.A. Bappy, M.D. Asfak-Ur-Rafi, M.D.S. Islam, A. Sajjad, K.N. Imran, and P.K. Saha, Design and development of unmanned aerial vehicle (Drone) for civil applications, (2015).
  • M. Schulzke and M. Schulzke, The drone revolution, the morality of drone warfare and the politics of regulation, (2017).
  • J. Ford, The history of drones (Drone history timeline from 1849 To 2018), DroneThusiast, 2018.
  • A.C. Watts, V.G. Ambrosia, and E.A. Hinkley, Unmanned aircraft systems in remote sensing and scientific research: Classification and considerations of use, Remote Sens. 6 (2012), pp. 1671–1692.
  • G. Singhal, B. Bansod, and L. Mathew, Unmanned Aerial Vehicle classification, Applications and challenges: a review, (2018).
  • R. Weibel and R.J. Hansman, Safety Considerations for Operation of Small Unmanned Aerial Vehicles in Civil Airspace, Iraq, 2003, published by the American Institute of Aeronautics and Astronautics, Inc., with permission.
  • W. Ren, J.S. Sun, R. Beard, and T. McLain, Experimental validation of an autonomous control system on a mobile robot platform, IET Control Theory Appl 1 (2007), pp. 1621–1629.
  • H. Ren, Y. Zhao, W. Xiao, and Z. Hu, A review of UAV monitoring in mining areas: Current status and future perspectives, Int. J. Coal Sci. Tech. 6 (2019), pp. 320–333.
  • H. Yang, Y. Lee, S.Y. Jeon, and D. Lee, Multi-rotor drone tutorial: Systems, mechanics, control and state estimation, Intell. Serv. Robo. (2017). doi:10.1007/s11370-017-0224-y.
  • W. Shyy, H. Aono, C. Kang, and H. Liu, An Introduction to flapping wing aerodynamics. 2013.
  • K. Dalamagkidis, K.P. Valavanis, L.A. Piegl, K. Dalamagkidis, K.P. Valavanis, and L.A. Piegl, Thoughts and recommendations on a UAS integration roadmap, on integrating unmanned aircraft systems into the national airspace system, (2012), pp. 161–191.
  • Civil aviation authority, aircraft icing handbook. 2000.
  • B.T. Clough, Unmanned aerial vehicles: Autonomous control challenges, a researcher’s perspective, J. Aerosp. Comput. Inf. Commun. 2 (2005). doi:10.2514/1.5588
  • H. Yao, R. Qin, and X. Chen, Unmanned aerial vehicle for remote sensing applications - A review, Remote Sens. (2019). doi:10.3390/rs11121443.
  • A. Berg, Detection and Tracking in Thermal Infrared Imagery. 2016.
  • M. Shan, F. Wang, F. Lin, Z. Gao, Y.Z. Tang, and B.M. Chen, Google map aided visual navigation for UAVs in GPS-denied environment, Zhuhai, China, IEEE International Conference on Robotics and Biomimetics, IEEE-ROBIO (2015) doi: 10.1109/ROBIO.2015.7418753.
  • Y.J. Wang, F. Tian, Y. Huang, J. Wang, and C.J. Wei, Monitoring coal fires in Datong coalfield using multi-source remote sensing data, Trans. Nonferrous Met. Soc. China 14 25 (2015), pp. 3421–3428.
  • T. Liu, et al., Estimates of rice lodging using indices derived from UAV visible and thermal infrared images, Agric. For. Meteorol. 252 (2018), pp. 144–154.
  • Z. Li, Z. Chen, L. Wang, J. Liu, and Q. Zhou, Area extraction of maize lodging based on remote sensing by small unmanned aerial vehicle, Nongye Gongcheng Xuebao/Transactions Chinese Soc. Agric. Eng. 9 (2014), pp. 207–213.
  • J.A.J. Berni, P.J. Zarco-Tejada, L. Suárez, V. González-Dugo, and E. Fereres, Remote sensing of vegetation from UAV platforms using lightweight multispectral and thermal imaging sensors, Int. Arch. Photogramm. Remote Sens. Spat. Inform. Sci. 19 (2009), pp. 193–208.
  • P. Rossi, F. Mancini, M. Dubbini, F. Mazzone, and A. Capra, Combining nadir and oblique uav imagery to reconstruct quarry topography: methodology and feasibility analysis, Eur. J. Remote Sens. 50 (2017), pp. 1211–1221.
  • M. Uysal, A.S. Toprak, and N. Polat, PHOTO REALISTIC 3D MODELING WITH UAV: GEDİK AHMET PASHA MOSQUE IN AFYONKARAHİSAR, ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci XL-5/W2 (2013), pp. 659–662.
  • Z.H. Xu, L.X. Wu, S.J. Chen, and Z. Wang, Method of engineering volume monitoring and calculation for open-pit mine from UAV images, Dongbei Daxue Xuebao/J. Northeast. Univ. 37 (2016), pp. 84–88.
  • M. Francioni, R. Salvini, D. Stead, R. Giovannini, S. Riccucci, C. Vanneschi, and D. Gullì, An integrated remote sensing-GIS approach for the analysis of an open pit in the Carrara marble district, Italy: slope stability assessment through kinematic and numerical methods, Comput. Geotech. 67 (2015), pp. 46–63.
  • I.R.N.P. Kumar, Unlocking the potentiality of UAVs in mining industry and its Implications, Int. J. Innov. Res. Sci. Eng. Technol 4 (2015), pp. 852–855.
  • R. Mlambo, I.H. Woodhouse, F. Gerard, and K. Anderson, Structure from motion (SfM) photogrammetry with drone data: A low cost method for monitoring greenhouse gas emissions from forests in developing countries, Forests (2017). doi:10.3390/f8030068.
  • J.P. Dash, M.S. Watt, G.D. Pearse, M. Heaphy, and H.S. Dungey, Assessing very high resolution UAV imagery for monitoring forest health during a simulated disease outbreak, ISPRS J. Photogramm. Remote Sens. 131 (2017), pp. 1–14.
  • A.H. Reddy, B. Kalyan, and C.S.N. Murthy, Mine rescue robot system – a review, Procedia Earth Planet. Sci. 11 (2015), pp. 457–462.
  • J.I.N. Wei, G.E. Hong-li, and D.U. Hua-qiang, A review on unmanned aerial vehicle remote sensing and its application [J], Remote Sens. 1 (2009), pp. 88-92.
  • V. Otero, V.D. Ruben, K.B. Satyanarayanaa, C. Martínez-Espinosaa, M.A.B. Fisolc, M.R.B. Ibrahimc, I. Sulong, H. Mohd-Lokman, R. Lucasd, and F. Dahdouh-Guebas, Managing mangrove forests from the sky: Forest inventory using field data and unmanned aerial vehicle (UAV) imagery in the matang mangrove forest reserve, peninsular Malaysia, For. Ecol. Manage 411 (2018), pp. 35–45.
  • J. Ridge, A. Seymour, A.B. Rodriguez, J. Dale, E. Newton, and D.W. Johnston, Advancing UAS methods for monitoring coastal environments, paper presented at AGU Fall Meeting, New Orleans, Dec 11–15. (2017).
  • J. Zhang, J. Hu, J. Lian, Z. Fan, X. Ouyang, and W. Ye, Seeing the forest from drones: Testing the potential of lightweight drones as a tool for long-term forest monitoring, Biol. Conserv. 198 (2016), pp. 60–69.
  • D.R.A. Almeida, E.N. Broadbent, A.M.A. Zambrano, B.E. Wilkinson, M.E. Ferreira, R. Chazdon, P. Meli, E.B. Gorgens, C.A. Silva, S.C. Stark, R. Valbuena, D.A. Papa, and P.H.S. Brancalion, Monitoring the structure of forest restoration plantations with a drone-lidar system, Int. J. Appl. Earth Obs. Geoinf. 79 (2019), pp. 192–198.
  • A. Hern, DHL launches first commercial drone ‘parcelcopter’ delivery service, Pharmaceuticals industry. The Guardian, 2014.
  • M. Moshref-Javadi and S. Lee, Using drones to minimize latency in distribution systems, 67th Annual Conference and Expo of the Institute of Industrial Engineers, Pitsburgh, PA, USA, (2017).
  • M.R. Haque, M. Muhammad, D. Swarnaker, and M. Arifuzzaman Autonomous quadcopter for product home delivery, 1st International Conference on Electrical Engineering and Information and Communication Technology, ICEEICT, Dhaka, Bangladesh, 2014, doi: 10.1109/ICEEICT.2014.6919154.
  • W.C. Chiang, Y. Li, J. Shang, and T.L. Urban, Impact of drone delivery on sustainability and cost: realizing the UAV potential through vehicle routing optimization, Appl. Energy. 242 (2019), pp. 1164–1175.
  • E. Ackerman and E. Strickland, Medical delivery drones take flight in east Africa, IEEE Spectr. (2018). doi:10.1109/MSPEC.2018.8241731.
  • M. Balasingam, Drones in medicine—The rise of the machines, Int. J. Clin. Pract (2017). doi:10.1111/ijcp.12989.
  • W. Yoo, E. Yu, and J. Jung, Drone delivery: Factors affecting the public’s attitude and intention to adopt, Telemat. Informatics 6 (2018), pp. 1687–1700.
  • U.T.M. NASA: Air traffic management for low-altitude drones, (2018).
  • D.E. Smith, W.L. Sjogren, G.L. Tylter, G. Balmino, F.G. Lemoine, and A.S. Konopliv, The gravity field of mars: results from mars global surveyor, Science 286 (1999), pp. 94–97.
  • M. Hassanalian, D. Rice, and A. Abdelkefi, Evolution of space drones for planetary exploration: A review, Prog. Aerosp. Sci. 97 (2018), pp. 61–105.
  • C. Hallewas and A. Momont, TU Delft’s ambulance drone drastically increases chances of survival of cardiac arrest patients, Delft University of Technology, 2014.
  • C. Wiltz, Ambulance drone could save lives, des. News, 2015.
  • S. Hayat, E. Yanmaz, T.X. Brown, and C. Bettstetter, Multi-objective UAV path planning for search and rescue, Proceedings - IEEE International Conference on Robotics and Automation, Singapore, Singapore, 2017, doi: 10.1109/ICRA.2017.7989656.
  • T. Fettermann, L. Fiori, M. Bader, A. Doshi, D. Breen, K.A. Stockin, and B. Bollard, Behaviour reactions of bottlenose dolphins (Tursiops truncatus) to multirotor unmanned aerial vehicles (UAVs), Sci. Rep. 8558 (2019). doi:10.1038/s41598-019-44976-9
  • C. Wefelscheid, R. Hänsch, and O. Hellwich, Three-dimensional building reconstruction using images obtained by unmanned aerial vehicles, ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci XXXVIII-1/C22 (2011), pp. 183–188.
  • D. Roca, S. Lagüela, L. Díaz-Vilariño, J. Armesto, and P. Arias, Low-cost aerial unit for outdoor inspection of building façades, Autom. Constr 36 (2013), pp. 128–135.
  • J. Liu, M. Jennesse, and P. Holley, Utilizing light unmanned aerial vehicles for the inspection of curtain walls: a case study, construction research congress 2016: old and new construction technologies converge in historic San Juan. Proceedings of the 2016 Construction Research Congress, CRC, San Juan, Puerto Rico, (2016), doi: 10.1061/9780784479827.264.
  • D. Kang and Y.J. Cha, Autonomous UAVs for structural health monitoring using deep learning and an ultrasonic beacon system with geo-tagging, Comput. Civ. Infrastruct. Eng, 00 (2018), pp. 1–18.
  • C. Eschmann, C.-M. Kuo, C.-H. Kuo, and C. Boller, High-resolution multisensor infrastructure inspection with unmanned aircraft systems, ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci XL-1/W2 (2013), pp. 125–129.
  • G. Morgenthal and N. Hallermann, Quality assessment of unmanned aerial vehicle (UAV) based visual inspection of structures, Adv. Struct. Eng (2014). doi:10.1260/1369-4332.17.3.289.
  • U. Niethammer, M.R. James, S. Rothmund, J. Travelletti, and M. Joswig, UAV-based remote sensing of the super-sauze landslide: evaluation and results, Eng. Geol 128 (2012), pp. 2–11.
  • S. Ruggles, J. Clark, K.W. Franke, D. Wolfe, B. Reimschiissel, R.A. Martin, T.J. Okeson, and J.D. Hedengren, Comparison of SfM computer vision point clouds of a landslide derived from multiple small UAV platforms and sensors to a TLS-based model, J. Unmanned Veh. Syst. 4 (2016). doi:10.1139/juvs-2015-0043
  • F. Carvajal, F. Agüera, and M. Pérez, Surveying a landslide in a road embankment using unmanned aerial vehicle photogrammetry, ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci XXXVIII-1/C22 (2012), pp. 201–206.
  • -C.-C. Liu, P.-L. Chen, T. Matsuo, and C.-Y. Chen, Rapidly responding to landslides and debris flow events using a low-cost unmanned aerial vehicle, J. Appl. Remote Sens. 9 (2015). doi:10.1117/1.jrs.9.096016
  • M. Car, D.J. Kaćunić, and M.-S. Kovačević, Application of unmanned aerial vehicle for landslide mapping, International Symposium on Engineering Geodesy, Varazdin, Croatia, (2016).
  • A.M. Samad, N. Kamarulzaman, M.A. Hamdani, T.A. Mastor, and K.A. Hashim. The potential of unmanned aerial vehicle (UAV) for civilian and mapping application, proceedings. 2013 IEEE 3rd International Conference on System Engineering and Technology, ICSET, Shah Alam, Malaysia, (2013), doi: 10.1109/ICSEngT.2013.6650191.
  • C.H. Hugenholtz, J. Walker, O. Brown, and S. Myshak, Earthwork volumetrics with an unmanned aerial vehicle and softcopy photogrammetry, J. Surv. Eng (2015). doi:10.1061/(ASCE)SU.1943-5428.0000138.
  • D.H. Kim, S.W. Kwon, S.W. Jung, S. Park, J.W. Park, and J.W. Seo, A study on generation of 3D model and mesh image of excavation work using UAV, 32nd International Symposium on Automation and Robotics in Construction and Mining: Connected to the Future, Proceedings, Oulu, Finland, (2015).
  • F. Alidoost and H. Arefi, An image-based technique for 3d building reconstruction using multi-view UAV images, in international archives of the photogrammetry, Remote Sens.Spatial Infor.Sci. ISPRS Arch. XL-1/W5 (2015), pp. 43–46.
  • K.P. Valavanis and G.J. Vachtsevanos, Handbook of Unmanned Aerial Vehicles, Handb. Unmanned Aer. Veh, 2015, Springer, Netherland, pp. 1–3022.
  • W.S. Hart and N.G. Gharaibeh, Use of micro unmanned aerial vehicles in roadside condition surveys, in T and DI congress 2011: integrated transportation and development for a better tomorrow. Proceedings of the 1st Congress of the Transportation and Development Institute of ASCE, Chicago, Illinois, (2011), doi: 10.1061/41167(398)9.
  • Y. Xu and Y. Turkan, Bridge inspection using bridge information modeling (BrIM) and unmanned aerial system (UAS). Advances in Informatics and Computing in Civil and Construction Engineering. (2019).
  • D. Wierzbicki, Application of unmanned aerial vehicles in monitoring of communication routes on country areas, Eng. Rural Dev. (2018). doi:10.22616/ERDev2018.17.N199.
  • K. Kanistras, G. Martins, M.J. Rutherford, and K.P. Valavanis, Survey of Unmanned Aerial Vehicles (Uavs) for Traffic Monitoring, Handbook of Unmanned Aerial Vehicles, 2015, Springer, Netherland.
  • H. Püschel, M. Sauerbier, and H. Eisenbeiss, A 3D model of castle landenberg (CH) from combined photogrametric processing of terrestrial and UAV based images, Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, XXXVII(B6b), (2008), pp. 93-98.
  • H. Yoon, J. Shin, and B.F. Spencer, Structural displacement measurement using an unmanned aerial system, Comput. Civ. Infrastruct. Eng. 33 (2018), pp. 183–192.
  • M. Scaioni, L. Barazzetti, and R. Brumana, RC-Heli and structure & motion techniques for the 3-D reconstruction of a Milan Dome spire, ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci. 38(5/W1), (2009), pp. 38.
  • D. Bulatov, P. Solbrig, H. Gross, P. Wernerus, E. Repasi, and C. Heipke, CONTEXT-BASED URBAN TERRAIN RECONSTRUCTION FROM UAV-VIDEOS FOR GEOINFORMATION APPLICATIONS, ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci XXXVIII-1/C22 (2011), pp. 75–80.
  • F. Xie, Z. Lin, D. Gui, and H. Lin, Study on construction of 3d building based on uav images, ISPRS - Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci XXXIX-B1 (2012), pp. 469–473.
  • R. Qin, A. Gruen, and X. Huang, UAV project - Building a reality-based 3D model of the NUS (National University of Singapore) campus, 33rd Asian Conference on Remote Sensing 2012, ACRS 2012, Pattaya, Thailand, (2012).
  • A. Gruen, X. Huang, R. Qin, T. Du, W. Fang, J. Boavida, and A. Oliveira, Joint processing of UAV imagery and terrestrial MMS data for very high resolution 3D city modeling, Gis. Science - Die Zeitschrift fur Geoinformatik, XL-1/W2, (2015), pp. 175-182.
  • M. Manyoky, P. Theiler, D. Steudler, and H. Eisenbeiss, Unmanned aerial vehicle in cadastral applications. ISPRS - Int. Arch. Photogramm, Remote Sens. Spat. Inf. Sci XXXVIII-1/C22 (2012), pp. 57–62.
  • F.J. Mesas-Carrascosa, M.D. Notario-García, M.D.N.G. de Larriva, M.S. de la Orden, and A.G.F. Porras, Validation of measurements of land plot area using UAV imagery, Int. J. Appl. Earth Obs. Geoinf. 33 (2014), pp. 270–279.
  • A. Vetrivel, M. Gerke, N. Kerle, and G. Vosselman, “Segmentation of UAV-based images incorporating 3D point cloud information,” International Archives of the Photogrammetry. Remote Sensing and Spatial Information Sciences - ISPRS Archives, XL-3/W2, (2015) pp. 261–268.
  • G.J.M. Kruijff, V. Tretyakov, T. Linder, F. Pirri, M. Gianni, E. Pianese, and S. Corrao, Rescue robots at earthquake-hit Mirandola, Italy: A field report, 2012 IEEE International Symposium on Safety, Security, and Rescue Robotics, SSRR 2012, (2012), College Station, TX, USA. doi: 10.1109/SSRR.2012.6523866.
  • C. Achille, A. Adami, S. Chiarini, S. Cremonesi, F. Fassi, L. Fregonese, and L. Taffurelli, UAV-based photogrammetry and integrated technologies for architectural applications—methodological strategies for the after-quake survey of vertical structures in Mantua (Italy), Sensors (Switzerland) (2015). doi:10.3390/s150715520.
  • A. Puri, A survey of unmanned aerial vehicles (UAV) for traffic surveillance, Dep. Comput. Sci. Eng. Uni. South Florida, (2005). .
  • S.M. Adams, M.L. Levitan, and C.J. Friedland, High resolution imagery collection for post-disaster studies utilizing unmanned aircraft systems (UAS), Photogramm. Eng. Remote Sensing 12 (2014), pp. 1161–1168.
  • C.A.F. Ezequiel, M. Cua, N.C. Libatiquel, G.L. Tangonan, R. Alampay, R.T. Labuguen, C.M. Favila, J.E. Honrado, V. Canos, C. Devaney, A.B. Loreto, J. Bacusmo, and B. Palma, UAV aerial imaging applications for post-disaster assessment, environmental management and infrastructure development. International Conference on Unmanned Aircraft Systems, ICUAS 2014 , (2014), Orlando FL, USA. doi: 10.1109/ICUAS.2014.6842266.
  • K.O. Said, M. Onifade, and A.I. Lawal, Computational intelligence-based models for predicting the spontaneous combustion liability of coal, Int. J. Coal Prep. Util. (2020), pp. 1–25. doi:10.1080/19392699.2020.1741558.
  • K.S. Osasan and T.B. Afeni, Review of surface mine slope monitoring techniques, J. Min. Sci. 46, 2 (2010), 10.1007/s10913-010-0023-8.
  • C.D. Martin, P.K. Kaiser, D.D. Tannant, and S. Yazici, Stress path and instability around mine openings, 9th ISRM Congress, (1999). Paris, France.
  • C.F. Cole and R.L. Kerch, Air quality management. (1990).
  • P.M.B. Pillai, Naturally occurring radioactive material (NORM V),Proc. Fifth Int. Symp. (2007) pp, 19–22. Seville, Spain.
  • R. Jackisch, S. Lorenz, R. Zimmermann, R. Möckel, and R. Gloaguen, Drone-borne hyperspectral monitoring of acid mine drainage: An example from the Sokolov lignite district, Remote Sens (2018). doi:10.3390/rs10030385.
  • I. Colomina and P. Molina, Unmanned aerial systems for photogrammetry and remote sensing: A review, ISPRS J. Photogramm. Remote Sensi. 92 (2014), pp. 79–97.
  • M. Sayab, D. Aerden, M. Paananen, and P. Saarela, 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). doi:10.3390/rs10081296.
  • J. Chen, K. Li, K.J. Chang, G. Sofia, and P. Tarolli, Open-pit mining geomorphic feature characterisation, Int. J. Appl. Earth Obs. Geoinf. 42 (2015), pp. 76–86.
  • B. Ruzgiene, T. Berteška, S. Gečyte, E. Jakubauskiene, and V.Č. Aksamitauskas, The surface modelling based on UAV photogrammetry and qualitative estimation, Meas. J. Int. Meas. Confed (2015). doi:10.1016/j.measurement.2015.04.018.
  • G. Esposito, G. Mastrorocco, R. Salvini, M. Oliveti, and P. Starita, Application of UAV photogrammetry for the multi-temporal estimation of surface extent and volumetric excavation in the Sa Pigada Bianca open-pit mine, Sardinia, Italy, Environ. Earth Sci (2017). doi:10.1007/s12665-017-6409-z.
  • S. Lee and Y. Choi, Reviews of unmanned aerial vehicle (drone) technology trends and its applications in the mining industry, Geosystem Eng. 19 (2016), pp. 197–204.
  • D.C. Jhariya, R. Khan, and G.S. Thakur, Impact of mining activity on water resource : an overview study, National Seminar on Recent Practices and Innovationsin Mining Industry (RPIMI,2016), Raipur, India.
  • L.J. Donnelly, H. De La Cruz, I. Asmar, O. Zapata, and J.D. Perez, The monitoring and prediction of mining subsidence in the Amaga, Angelopolis, Venecia and Bolombolo Regions, Antioquia, Colombia, Eng. Geol 59 (2001), pp. 103–114.
  • C. Huang, S.N. Goward, J.G. Masek, N. Thomas, Z. Zhu, and J.E. Vogelmann, An automated approach for reconstructing recent forest disturbance history using dense Landsat time series stacks, Remote Sens. Environ. 114 (2010), pp. 183–198.
  • R.G. Darmody, R.T. Hetzler, and F.W. Simmons, Coal mine subsidence: Effects of mitigation on crop yields, Int. J. Surf. Mining, Reclam. Environ. 59 (1992), pp. 187–190.
  • H. Ren, Y. Zhao, W. Xiao, and Z. Hu, A review of UAV monitoring in mining areas: Current status and future perspectives, Int. J. Coal Sci. Technol. 6 (2019), pp. 320–333.
  • A.C. Keatleya, P.G. Martina, K.R. Hallama, O.D. Paytona, R. Awberyb, F. Carvalhoc, J.M. Oliveirac, L. Silvac, M. Maltac, and T.B. Scotta, Source identification of uranium-containing materials at mine legacy sites in Portugal, J. Environ. Radioact. 183 (2018), pp. 102–111.
  • J. Bendiga, K. Yua, H. Aasena, A. Boltena, S. Bennertz, J. Broscheit, M.L. Gnypa, and G. Baretha, Combining UAV-based plant height from crop surface models, visible, and near infrared vegetation indices for biomass monitoring in barley, Int. J. Appl. Earth Obs. Geoinf. 39 (2015), pp. 79–87.
  • S. Iverson and S. Signer, Assessment and detection of loose rock hazards in underground metal mines using thermal imaging, 2014 SME Annual Meeting and Exhibit, SME 2014: Leadership in Uncertain Times, (2014). Salt Lake City, Utah, USA.
  • K.O. Said, M. Onifade, A.I. Lawal, and J.M. Githiria, An Artificial intelligence-based model for the prediction of spontaneous combustion liability of coal based on its proximate analysis, Combust. Sci. Technol (2020), pp. 1–18.https://doi.org/10.1080/00102202.2020.1736577.
  • M. Onifade and B. Genc, A review of spontaneous combustion studies–South African context, Int. J. Mining, Reclam. Environ 33 (2019), pp. 527–547.
  • M.C. Harvey, J.V. Rowland, and K.M. Luketina, Drone with thermal infrared camera provides high resolution georeferenced imagery of the Waikite geothermal area, New Zealand, J. Volcanol. Geotherm. Res (2016). doi:10.1016/j.jvolgeores.2016.06.014.
  • R.M. Turner, N.P. Bhagwat, L.J. Galayda, C.S. Knoll, E.A. Russell, and M.M. MacLaughlin, Geotechnical characterization of underground mine excavations from UAV-captured photogrammetric & thermal imagery, 52nd U.S. Rock Mech. Symp. Seattle, Washington, (2018).
  • D. Hausamann, W. Zirnig, G. Schreier, and P. Strobl, Monitoring of gas pipelines – A civil UAV application, Aircr. Eng. Aerosp. Technol. 77 (2005), pp. 352–360.
  • M. Rossi, D. Brunelli, A. Adami, L. Lorenzelli, F. Menna, and F. Remondino, Gas-drone: Portable gas sensing system on UAVs for gas leakage localization, Proc IEEE Sens (2014). doi:10.1109/ICSENS.2014.6985282.
  • W. Xiao, J. Chen, H. Da, H. Ren, J. Zhang, and L. Zhang, Inversion and analysis of maize biomass in coal mining subsidence area based on UAV images, Nongye Jixie Xuebao/Transactions Chinese Soc. Agric. Mach. 8 (2018), pp. 169–180.
  • D.V. Beregovoi, J.A. Younes, and M.G. Mustafin, Monitoring of quarry slope deformations with the use of satellite positioning technology and unmanned aerial vehicles, Procedia Eng. (2017). doi:10.1016/j.proeng.2017.05.116.
  • N. Ngadiman, I.A. Badrulhissham, M. Mohamad, N. Azhari, M. Kaamin, and N.B. Hamid, Monitoring slope condition using UAV technology, Civ. Eng. Archit. 7, 6 (2019), pp. 1–6. doi:10.13189/cea.2019.071401.
  • S. Wang, Z. Ahmed, M.Z. Hashmi, and W. Pengyu, Cliff face rock slope stability analysis based on unmanned arial vehicle (UAV) photogrammetry, Geomech. Geophys. Geo-Energy Geo-Res 5 (2019), pp. 333–344.
  • Z. Hu, C. Chen, W. Xiao, X. Wang, and M. Gao, Surface movement and deformation characteristics due to high-intensive coal mining in the windy and sandy region, Int. J. Coal Sci. Technol. 3 (2016), pp. 339–348.
  • W. Xiao, Z. Hu, and Y. Fu, Zoning of land reclamation in coal mining area and new progresses for the past 10 years, Int. J. Coal Sci. Technol 1 (2014), pp. 177–183.
  • T.G. Whiteside and R.E. Bartolo, A robust object-based woody cover extraction technique for monitoring mine site revegetation at scale in the monsoonal tropics using multispectral RPAS imagery from different sensors, Int. J. Appl. Earth Obs. Geoinf. 73 (2018), pp. 300–312.
  • K. Johansen, P.D. Erskine, and M.F. McCabe, Using unmanned aerial vehicles to assess the rehabilitation performance of open cut coal mines, J. Clean. Prod (2019). doi:10.1016/j.jclepro.2018.10.287.
  • J.C. Padró, V. Carabassa, J. Balagué, L. Brotons, J.M. Alcañiz, and X. Pons, Monitoring opencast mine restorations using Unmanned Aerial System (UAS) imagery, Sci. Total Environ. 657 (2019), pp. 1602–1614.
  • G. Pajares, Overview and current status of remote sensing applications based on unmanned aerial vehicles (UAVs), Photogramm. Eng. Remote Sensing (2015). doi:10.14358/PERS.81.4.281.
  • A. Rauhala, A. Tuomela, C. Davids, and P.M. Rossi, UAV remote sensing surveillance of a mine tailings impoundment in Sub-Arctic conditions, Remote Sens 9 (2017), pp. 1–14.
  • P.G. Martin, O.D. Payton, J.S. Fardoulis, D.A. Richards, and T.B. Scott, The use of unmanned aerial systems for the mapping of legacy uranium mines, J, Environ. Radioact. 143 (2015), pp. 135–140. doi:10.1016/j.jenvrad.2015.02.004
  • J. Suh and Y. Choi, Mapping hazardous mining-induced sinkhole subsidence using unmanned aerial vehicle (drone) photogrammetry, Environ. Earth Sci (2017). doi:10.1007/s12665-017-6458-3.
  • A. Stumpf, J.P. Malet, P. Allemand, and P. Ulrich, Surface reconstruction and landslide displacement measurements with Pléiades satellite images, ISPRS J. Photogramm. Remote Sens. 95 (2014), pp. 1–12.
  • X. Tong, et al., Integration of UAV-based photogrammetry and terrestrial laser scanning for the three-dimensional mapping and monitoring of open-pit mine areas, Remote Sens. 7 (2015), pp. 6635–6662.
  • J.M. Fernández-Guisuraga, E. Sanz-Ablanedo, S. Suárez-Seoane, and L. Calvo, Using unmanned aerial vehicles in postfire vegetation survey campaigns through large and heterogeneous areas: opportunities and challenges, Sensors (Switzerland) (2018). doi:10.3390/s18020586.
  • L. Wallace, A. Lucieer, Z. Malenovskỳ, D. Turner, and P. Vopěnka, Assessment of forest structure using two UAV techniques: A comparison of airborne laser scanning and structure from motion (SfM) point clouds, Forests (2016). doi:10.3390/f7030062.
  • A. Salach, K. Bakula, M. Pilarska, W. Ostrowski, K. Górski, and Z. Kurczynski, Accuracy assessment of point clouds from LidaR and dense image matching acquired using the UAV platform for DTM creation, ISPRS Int. J. Geo-Information. 7 (2018), pp. 342–358.
  • The fleye drone could be the safest flying robot at CES|engadget. Available at https://www.engadget.com
  • Flybotix–professional portable drone. Available at https://flybotix.com/
  • Fleye|Home. Available at https://www.gofleye.com/(accessed on 27 September 2019
  • H. Shakhatreh, et al., Unmanned Aerial Vehicles (UAVs): a survey on civil applications and key research challenges, IEEE Access. 7(2019),48572–48634. doi:10.1109/ACCESS.2019.2909530.
  • M. Mozaffari, W. Saad, M. Bennis, Y.H. Nam, and M. Debbah, A tutorial on UAVs for wireless networks: applications, challenges, and open problems, IEEE Commun. Surv. Tutorials. (2019). doi:10.1109/COMST.2019.2902862.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.