Particularities of deformation processes solution with GIS application for mining landscape reclamation in East Slovakia

Sedlak Vladimír, Poljakovic Peter

Article ID: 508
Vol 4, Issue 2, 2021, Article identifier:90-101

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Abstract


The influence of mining activity on the environment on the environment belongs to the most negative industrial influences. Mine subsidence on the surface can be a result of many deep underground mining activities. The present study offers the theory to the specific case of the deformation vectors solution in a case of disruption of the data homogeneity of the geodetic network structure in the monitoring station during periodical measurements in mine subsidence. The theory was developed for the mine subsidence at the abandoned magnesite mine of Košice-Bankov near the city of Košice in East Slovakia. The outputs from the deformation survey were implemented into geographical information system (GIS) applications to a process of gradual reclamation of whole mining landscape in the magnesite mine vicinity. After completion of the mining operations and liquidation of the mine company, it was necessary to determine the exact edges of the mine subsidence of Košice-Bankov with the zones of residual ground motion in order to implement a comprehensive reclamation of the devastated mining landscape. Requirement of knowledge about stability of the former mine subsidence was necessary for starting the reclamation work. Outputs from the present specific solutions of the deformation vectors confirmed the multi-year stability of the mine subsidence in the area of interest. Some numerical and graphical results from the deformation vectors survey in the abandoned magnesite mine of Košice-Bankov are presented. The obtained results were transformed into GIS for the needs of the municipality of Košice City to the implementation of the reclamation activities in the mining territory of Košice-Bankov.


Keywords


Mine Subsidence; Deformation Vector; Geodetic Network; GIS; Reclamation

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References


Cui X, Miao X, Wang J, et al. Improved prediction of differential subsidence caused by underground mining. International Journal of Rock Mechanics and Mining Sciences 2000; 37(4): 615–627.

Díaz-Fernández ME, Álvarez-Fernández MI, Álvarez-Vigil AE. Computation of influence functions for automatic mine subsidence prediction. Computational Geosciences 2010; 14(1): 83–103.

Djamaluddin I, Mitani Z, Esaki T. Evaluation of ground movement and damage to structures from Chinese coal mining using a new GIS coupling model. International Journal of Rock Mechanics and Mining Sciences 2011; 48(3): 380–393.

Knothe S. Forecasting the influence of mining (in Polish). Katowice: Śląsk Publishing House; 1984.

Kratzsch H. Mine subsidence engineering. Heidelberg: Springer-Verlag GmbH; 1983.

Reddish DJ, Whittaker BN. Subsidence: Occurrence, prediction and control. Amsterdam: Elsevier; 1989.

Donnelly LJ, Reddish DJ. Engineering Geology (in Polish). 1994; 34(3/4): 243–255.

Bauer RA, Trent BA, Dumontelle PB. Mine subsidence in Illinois: Facts for homeowners. In: Illinois state geological survey. Illinois: ISGS Publising; 2013. p. 20.

Colorado Geological Survey. Subsidence mine [Internet]. Colorado Geological Survey website [cit. 26 Sep. 2016]. Available from: http://Coloradogeo logicalsurvey.org/geologic-hazards/subsidence-min/

Pinto G, et al. Subsidence [Internet]. Illinois Department of Natural Resources website, [cited 30 May 2016]. Available from: https://www.dnr.illinois. gov/mines/AML/Pages/ Subsidence.aspx.

Alehossein H. Back of envelope mine subsidence estimation. Australian Geomechanics: Australian Geomechanics Journal 2009; 44 (1): 29–32.

Jung HC, Kim SW, Jung HS, et al. Satellite observation of coal mining subsidence by persistent scatterer analysis. Engineering Geology 2007; 92(1- 2): 1–13.

Sedlák V. Measurement and prediction of land subsidence above longwall coal mines, Slovakia. In: Borchers WJ (editor). Land subsidence/case studies and current research. Belmont: U.S. Geological Survey; 1998. p. 257–263.

Cai J, Wang J, Wu J, et al. Horizontal deformation rate analysis based on multiepoch GPS measurements in Shanghai. Journal of Surveying Engineering 2008; 134(4): 132–137.

Can E, Mekik Ç, Kuşçu Ş, et al. Computation of subsidence parameters resulting from layer movements post-operations of underground mining. Journal of Structural Geology 2013; 47: 16–24.

Hu L. Gradual deformation and iterative calibration of Gaussian-related stochastic models. Mathematical Geology 2000; 32(1): 87–108.

Lu W, Cheng S, Yang H, et al. Application of GPS technology to build a mine-subsidence observation station. Journal of China University of Mining & Technology 2008; 8(3): 377–380.

Marschalko M, Fuka M, Treslin L. Measurements by the method of precise inclinometry on locality affected by mining activity. Archives of Mining Sciences 2008; 53(3): 397–414.

Ng AHM, Ge L, Zhang K, et al. Deformation mapping in three dimensions for underground mining using InSAR—Southern highland coalfield in New South Wales, Australia. International Journal of Remote Sensing 2011; 32(22): 7227–7256.

Sedlák V. Possibilities of modelling surface movements in GIS in the Košice depression, Slovakia. RMZ—Materials and Geoenvironment 2004; 51(4): 2127–2133.

Wright P, Stow R. Detecting mine subsidence from space. International Journal of Remote Sensing 1999; 20(6): 1183–1188.

Konicek P, Soucek K, Stas L, et al. Long-hole destress blasting for rockburst control during deep underground coal mining. International Journal of Rock Mechanics and Mining Sciences 2013; 61: 141–153.

Strazalowski P, Scigala R. The example of linear discontinuous deformations caused by underground extraction. Transection of VŠB—Technical University Ostrava. Civil Engineering, Series 2005; (2): 193–198.

Li P, Tan Z, Deng K. Calculation of maximum ground movement and deformation caused by mining. Transactions of Nonferrous Metals Society of China 2011; 21(Sup. 3): 562–569.

Christensen R. General Gauss–Markov models. In: Christensen R (editor). Plane answers to complex questions: The theory of linear models. 4th ed. New York: Springer; 2011. p. 237–266.

Gene H, Golub CF, Van Loan. Matrix computations. Baltimore: JHU Press, 2013

Groß J. The general Gauss-Markov model with possibly singular dispersion matrix. Statistical Papers 2004; 45(3): 311–336.

Lindgren F, Ruel H, Lindström J. An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 2011; 73(4): 423–498.

Lehmann EL, Romano JP. Testing statistical hypotheses. 3rd ed. New York: Springer; 2005. p. 784.

Blachowski J. Application of GIS spatial regression methods in assessment of land subsidence in complicated mining conditions: Case study of the Walbrzych coal mine (SW Poland). Natural Hazards 2016; 84: 1–18.

Yang K, Xiao J, Duan M, et al. Geo-deformation information extraction and GIS analysis on important buildings by underground mining subsidence. In: 2009 International Conference on Information Engineering and Computer Science—ICIECS 2009. Wuhan: IEEE; 2009.

Yang KM, Ma JT, Pang B, et al. 3D visual technology of geo-deformation disasters induced by mining subsidence based on ArcGIS engine. Key Engineering Materials 2012; 500: 428–436.




DOI: http://dx.doi.org/10.24294/jgc.v4i2.508

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