Application of the GNSS Method in the Monitoring of Mine Surface Displacement: A Systemic Review

Nguyen, Hai Van; Pham, Khai Cong; Nguyen, Dung Ba; Nguyen, Long Quoc

doi:10.29227/IM-2024-01-115

Artykuł - szczegóły

Tytuł artykułu

Application of the GNSS Method in the Monitoring of Mine Surface Displacement: A Systemic Review

Autorzy

Nguyen Hai Van , Pham Khai Cong , Nguyen Dung Ba , Nguyen Long Quoc

Treść / Zawartość

Pełne teksty:

Pobierz

Identyfikatory

DOI

10.29227/IM-2024-01-115

Warianty tytułu

Zastosowanie metody GNSS w monitorowaniu przemieszczeń powierzchni kopalni: przegląd systemowy

Języki publikacji

Abstrakty

Currently, Global Navigation Satellite System (GNSS) techniques are widely used for monitoring displacement. This study provides an overview of current developments in the application of GNSS technology for determining displacement based on the findings of 52 research publications over the past fifteen years, from 2009 to August 2024. The obtained results indicated that RTK-GNSS and PPP-GNSS are effective methods to monitor deformation, subsidence, and landslides in open-pit, underground, abandoned mines, and waste dumps. Besides, some limitations and benefits of this technology have been mentioned in this paper. Finally, the prospects of developing of GNSS technique combined with AI technology in displacement monitoring of mining areas were also presented. This paper offers a technical reference for expanding the understanding and knowledge of GNSS applications in detecting displacement in mining areas.

Obecnie do monitorowania przemieszczeń powszechnie stosuje się techniki Globalnego Systemu Nawigacji Satelitarnej (GNSS). Niniejsza praca stanowi przegląd aktualnego rozwoju zastosowań technologii GNSS do wyznaczania przemieszczeń na podstawie wniosków z 50 publikacji naukowych z ostatnich piętnastu lat, od 2009 r. do sierpnia 2024 r. Uzyskane wyniki wskazują, że RTK-GNSS i PPP-GNSS są skuteczne metody monitorowania deformacji, osiadań i osuwisk w kopalniach odkrywkowych, podziemnych, opuszczonych kopalniach i na składowiskach odpadów. Poza tym w artykule wspomniano o pewnych ograniczeniach i zaletach tej technologii. Na koniec przedstawiono także perspektywy rozwoju techniki GNSS w połączeniu z technologią AI w monitorowaniu przemieszczeń obszarów górniczych. W artykule przedstawiono odniesienia techniczne umożliwiające poszerzenie zrozumienia i wiedzy na temat zastosowań GNSS w wykrywaniu przemieszczeń na obszarach górniczych.

Słowa kluczowe

displacement deformation subsidence landslide mine area GNSS

przemieszczenie deformacja osiadanie osuwisko teren kopalni GNSS

Wydawca

Polskie Towarzystwo Przeróbki Kopalin

Czasopismo

Inżynieria Mineralna

Rocznik

2024

Tom

Vol. 2, no. 1

Strony

247--255

Opis fizyczny

Bibliogr. 52 poz., rys.

Twórcy

autor

Nguyen Hai Van

haingv@tlu.edu.vn

Faculty of Water Resources Engineering, ThuyLoi University, Vietnam

autor

Pham Khai Cong

Faculty of Geomatics and Land Administration, Hanoi University of Mining and Geology, Vietnam

autor

Nguyen Dung Ba

Faculty of Surveying, Mapping and Geographic Information, Hanoi University of Natural Resources and Environment, Vietnam

autor

Nguyen Long Quoc

Innovations for Sustainable and Responsible Mining (ISRM) Research Group, Hanoi University of Mining and Geology, Vietnam

Bibliografia

1. Owczarz, K. A review of geodetic and remote sensing methods used for detecting surface displacements caused by mining. in IOP Conference Series: Earth and Environmental Science. 2020. IOP Publishing.
2. Lian, X., et al., Determination of the stability of high-steep slopes by global navigation satellite system (GNSS) real-time monitoring in long wall mining. Applied Sciences, 2020. 10(6): p. 1952.
3. Lu, C. The Application of Satellite Navigation System in Deformation Monitoring. in Journal of Physics: Conference Series. 2021. IOP Publishing.
4. Jing-Xiang, G., H.J.P.E. Hong, and P. Science, Advanced GNSS technology of mining deformation monitoring. 2009. 1(1): p. 1081-1088.
5. Heimlich, C., et al., Uplift around the geothermal power plant of Landau (Germany) as observed by InSAR monitoring. 2015. 3: p. 1-12.
6. Bovenga, F., et al., Using C/X-band SAR interferometry and GNSS measurements for the Assisi landslide analysis. 2013. 34(11): p. 4083-4104.
7. Mateus, P., et al., Experimental study on the atmospheric delay based on GPS, SAR interferometry, and numerical weather model data. 2012. 51(1): p. 6-11.
8. ONDREJKA, P., et al., Use of GNSS technology in engineering geology in Slovakia. 2011. 43(2): p. 111-120.
9. Del Soldato, M., et al., Review of works combining GNSS and InSAR in Europe. 2021. 13(9): p. 1684.
10. Kostyanev, S., et al., The use of GNSS technologies for application in mining, geology and geodesy in Bulgaria. 2010. 100: p. 525-534.
11. Behera, A. and K.S. Rawat, A Comprehensive Review on Mining Subsidence and its Geo-environmental Impact. Journal of Mines, Metals & Fuels, 2023. 71(9).
12. Suh, J., An overview of GIS-based assessment and mapping of mining-induced subsidence. Applied Sciences, 2020. 10(21): p. 7845.
13. Cai, Y., et al., A review of monitoring, calculation, and simulation methods for ground subsidence induced by coal mining. International Journal of Coal Science & Technology, 2023. 10(1): p. 32.
14. Hejmanowski, R., et al., An analysis applying InSAR of subsidence caused by nearby mining-induced earthquakes. Geosciences, 2019. 9(12): p. 490.
15. Yu, Y., et al., Subsidence mechanism and stability assessment methods for partial extraction mines for sustainable development of mining cities—A review. Sustainability, 2018. 10(1): p. 113.
16. Guzy, A. and A.A. Malinowska, Assessment of the impact of the spatial extent of land subsidence and aquifer system drainage induced by underground mining. Sustainability, 2020. 12(19): p. 7871.
17. Humphries, L., A review of relative sea level rise caused by mining-induced subsidence in the coastal zone: some implications for increased coastal recession. Climate research, 2001. 18(1-2): p. 147-156.
18. Qingsong, D., et al., Land Use Changes in High Cold-altitude Mining Area Based on Remote Sensing Technology. Environmental Science & Technology (10036504), 2020. 43(12).
19. Liu, P., et al., Impacts of Surface Deformation Induced by Underground Mining of Metal Mines on Above-Ground Structures: A Case Study. Minerals, 2023. 13(12): p. 1510.
20. Tondaś, D., K. Kazmierski, and J. Kapłon, Real-time and near real-time displacement monitoring with GNSS observations in the mining activity areas. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2023.
21. Jing-Xiang, G. and H. Hong, Advanced GNSS technology of mining deformation monitoring. Procedia Earth and Planetary Science, 2009. 1(1): p. 1081-1088.
22. Prokos, A. and C. Roumpos. Ground deformation monitoring techniques at continuous surface lignite mines. in 4th Joint International Symposium on Deformation Monitoring (JISDM). Athens, Greece. 2019.
23. Rodriguez-Lloveras, X., et al., Two decades of GPS/GNSS and DInSAR monitoring of Cardona salt mines (NE of Spain)–natural and mining-induced mechanisms and processes. Proceedings of the International Association of Hydro-logical Sciences, 2020. 382: p. 167-172.
24. Huang, G., S. Du, and D. Wang, GNSS techniques for real-time monitoring of landslides: A review. Satellite Navigation, 2023. 4(1): p. 5.
25. Liu, C., et al., Mine surface deformation monitoring using modified GPS RTK with surveying rod: Initial results. Survey Review, 2015. 47(341): p. 79-86.
26. GAO, J.-x., et al., A new method for mining deformation monitoring with GPS-RTK. Transactions of Nonferrous Metals Society of China, 2011. 21: p. s659-s664.
27. Issabek, T., V. Dyomin, and D. Ivadilinova, Methods for monitoring the earth surface displacement at points of small geodetic network under the underground method of coal development. Natsional'nyi Hirnychyi Universytet. Naukovyi Visnyk, 2019(2): p. 13-20.
28. Costantino, D. and M.G. Angelini, Geodetic monitoring applied to a mine area. Applied Geomatics, 2011. 3: p. 61-74.
29. Brown, N., S. Kaloustian, and M. Roeckle. Monitoring of open pit mines using combined GNSS satellite receivers and robotic total stations. in Slope Stability 2007: Proceedings of the 2007 International Symposium on Rock Slope Stability in Open Pit Mining and Civil Engineering. 2007. Australian Centre for Geomechanics.
30. Szczerbowski, Z. and J. Jura, Mining induced seismic events and surface deformations monitored by GPS permanent stations. Acta Geodyn. Geomater, 2015. 12(3): p. 179.
31. Sokoła-Szewioła, V. and Z. Siejka, Validation of the accuracy of geodetic automated measurement system based on GNSS platform for continuous monitoring of surface movements in post-mining areas. Reports on Geodesy and Geoin-formatics, 2021. 112.
32. Zhou, W., et al., An improved GNSS and InSAR fusion method for monitoring the 3D deformation of a mining area. IEEE Access, 2021. 9: p. 155839-155850.
33. Dai, S., et al., Prediction of Mining-Induced 3-D Deformation by Integrating Single-Orbit SBAS-InSAR, GNSS, and Log-Logistic Model (LL-SIG). IEEE Transactions on Geoscience and Remote Sensing, 2023. 61: p. 1-13.
34. Pawłuszek-Filipiak, K., et al., Assessing the application of GACOS atmospheric correction for DInSAR-based mining deformation monitoring by using Sentinel-1 data in Upper Silesian Coal Basin in Poland. Geodesy and Cartography, 2021. 70(2).
35. Palamà, R., et al., A multi-temporal small baseline interferometry procedure applied to mining-induced deformation monitoring. Remote Sensing, 2022. 14(9): p. 2182.
36. Du, Q., et al., Deformation monitoring in an alpine mining area in the Tianshan Mountains based on SBAS-InSAR technology. Advances in Materials Science and Engineering, 2021. 2021: p. 1-15.
37. Li, Y., et al., Deformation monitoring and analysis of Kunyang phosphate mine fusion with InSAR and GPS measurements. Advances in Space Research, 2022. 69(7): p. 2637-2658.
38. Tondaś, D., et al., Kalman filter-based integration of GNSS and InSAR observations for local nonlinear strong deformations. Journal of Geodesy, 2023. 97(12): p. 109.
39. Bo, H., et al., Estimation of ground subsidence deformation induced by underground coal mining with GNSS-IR. Remote Sensing, 2022. 15(1): p. 96.
40. Wang, G., et al., Mining subsidence prediction parameter inversion by combining GNSS and DInSAR deformation measurements. IEEE Access, 2021. 9: p. 89043-89054.
41. Tiwari, A., et al., Geodetic investigation of landslides and land subsidence: Case study of the Bhurkunda coal mines and the Sirobagarh landslide. Survey review, 2018.
42. Pham, C.K., D.T. Tran, and V.H. Nguyen, GNSS/CORS-Based Technology for Real-Time Monitoring of Landslides on Waste Dump–A Case Study at the Deo Nai South Dump, Vietnam. Inżynieria Mineralna, 2020. 1(2): p. 181-191.
43. Hu, H., et al., Land deformation monitoring in mining area with PPP-AR. 2014. 24(2): p. 207-212.
44. XU, C.-h., et al., Precise point positioning and its application in mining deformation monitoring. 2011. 21: p. s499-s505.
45. Li, R., et al., A New Method for Deformation Monitoring of Structures by Precise Point Positioning. Remote Sensing, 2023. 15(24): p. 5743.
46. Junshan, Y., et al., Adaptive filtering algorithm and its application based on the PPP technique for deformation monitoring in mining area. Bulletin of Surveying and Mapping, (9): p. 129.
47. Wang, D., et al., Stability analysis of reference station and compensation for monitoring stations in GNSS landslide monitoring. Satellite Navigation, 2023. 4(1): p. 29.
48. Lian, X., et al., Residual subsidence time series model in mountain area caused by underground mining based on GNSS online monitoring. International Journal of Coal Science & Technology, 2024. 11(1): p. 27.
49. Jagiwala, D. and S.N. Shah. Possibilities of AI Algorithm Execution in GNSS. in 2022 URSI Regional Conference on Radio Science (USRI-RCRS). 2022. IEEE.
50. Jiang, W., et al., A new deep self-attention neural network for GNSS coordinate time series prediction. GPS Solutions, 2024. 28(1): p. 3.
51. Seyed Mohammad Reza Mosavi and S.B. . Artificial Intelligence Applications in GNSS. The Journal of Global Navigation Satellite Systems, 2020.
52. Ji, P., et al., A new method to obtain 3-D surface deformations from InSAR and GNSS data with genetic algorithm and support vector machine. IEEE Geoscience and Remote Sensing Letters, 2021. 19: p. 1-5.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).

Typ dokumentu

Bibliografia

Identyfikator YADDA

bwmeta1.element.baztech-fbcfc411-a38f-45e2-bda9-0400d440853c