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ArticleName Determination procedure of linear parameters of movement processes from digital terrain models in Khibiny apatite–nepheline ore mining
DOI 10.17580/gzh.2023.05.14
ArticleAuthor Zherlygina E. S., Mustafin M. G., Vasiliev B. Yu., Nikolaev R. V.

Research Center for Geomechanics and Mining Practice Problems, Saint-Petersburg Mining
University, Saint-Petersburg, Russia:

E. S. Zherlygina, Senior Researcher, Candidate of Engineering Sciences,
M. G. Mustafin, Head of Department, Doctor of Engineering Sciences
B. Yu. Vasiliev, Post-Graduate Student–Researcher


Apatit’s Division in Kirovsk, Kirovsk, Russia:
R. V. Nikolaev, Chief Surveyor


Surveying of ground and underground movements aims to determine and adjust the displacement parameters, and the type and size of deformation of undermined objects. The authors describe application of digital terrain models to assess movement process parameters as a case-study of Khibiny apatite–nepheline ore mining. The possibility to determine linear parameters of movements in the ground surface area inaccessible using classical methods is illustrated. The source information was the aerial laser scanning data obtained in 2015 to 2020 in Rasvumchorr and Kukisvumchorr Mines. The data were classified using TerraSolid TerraScan tools. Then, the digital terrain models were constructed in Microstation. The further digital modeling of the terrain was carried out in Golden Software’s Surfer with spatial resolution and some spatial interpolation techniques. Using the resultant digital models, the surfaces were constructed in Autodesk AutoCAD. The surfaces were used to draw cross-sections in the coordinate grid in Rhinoceros 6. Over the observation period from 2015 to 2020, by the authors’ opinion, the method of kriging proved to be the best out of the methods tested in Rasvumchorr and Kukisvumchorr Mines. The method of spatial interpolation provided the least scatter of data, the lowest minimum and maximum deviations and the least mean square deviation in the majority of tests. The research findings allow expecting that the described methods can enable safe mining at the minimum time consumption.

keywords Digital terrain model, movement process parameters, surveying-based monitoring, spatial interpolation methods, point cloud, aerial laser scanning

1. Monika, Govil M. H., Chatterjee R. S., Bhaumik P., Vishwakarma N. Deformation monitoring of Surakachhar underground coal mines of Korba, India using SAR interferometry. Advances in Space Research. 2022. Vol. 70, Iss. 12. pp. 3905–3916.
2. Besoya M., Govil H., Bhaumik P. A review on surface deformation evaluation using multitemporal SAR interferometry techniques. Spatial Information Research. 2021. Vol. 29, Iss. 3. pp. 267–280.
3. El Kamali M., Saibi H., Abuelgasim A. Land surface deformation monitoring in the Al-Ain arid region (UAE) using microgravity and SAR interferometry surveys. Environmental Research. 2022. Vol. 212. 113505. DOI: 10.1016/j.envres.2022.113505
4. Varbla S., Ellmann A., Puust R. Centimeter-range deformations of built environment revealed by drone-based photogrammetry. Automation in Construction. 2021. Vol. 128. 103787. DOI: 10.1016/j.autcon.2021.103787

5. Devyatkov S. Yu. Estimation of earth surface deformations during pillar mining. Procedia Structural Integrity. 2021. Vol. 32. pp. 56–63.
6. Lu He, Di Wu, Linfeng Ma. Numerical simulation and verification of goaf morphology evolution and surface subsidence in a mine. Engineering Failure Analysis. 2022. Vol. 144. 106918. DOI: 10.1016/j.engfailanal.2022.106918
7. Shuyin Jiang, Gangwei Fan, Qizhen L i, Shizhong Zhang, Liang Chen. Effect of mining parameters on surface deformation and coal pillar stability under customized shortwall mining of deep extra-thick coal seams. Energy Reports. 2021. Vol. 7. pp. 2138–2154.
8. Kozyrev A. A., Demidov Yu. V., Maltsev V. A., Enyutin A. N., Aminov V. N. et al. Instructions on overlying rock caving control and protection of structures and nature from underground mining impact at Apatit JSC. Apatity, 2002. 51 p.
9. Ponomarenko M. R., Kutepov Yu. I., Shabarov A. N. Open pit mining monitoring support with information and analysis using web mapping technologies. GIAB. 2022. No. 8. pp. 56–70.
10. Karasev M. A., Protosenya A. G., Katerov A. M., Petrushin V. V. Analysis of shaft lining stress state in anhydrite–rock salt transition zone. Rudarsko-geološko-naftni zbornik. 2022. Vol. 37, No. 1. pp. 151–162.
11. Bykowa E., Skachkova M., Raguzin I., Dyachkova I., Boltov M. Automation of Negative Infrastructural Externalities Assessment Methods to Determine the Cost of Land Resources Based on the Development of a “Thin Client” Model. Sustainability. 2022. Vol. 14, Iss. 15. 9383. DOI: 10.3390/su14159383
12. Protosenya A. G., Katerov A. M. Development of stress and strain state of combined support for a vertical shaft driven in salt massif. GIAB. 2022. No. 6-1. pp. 100–113.
13. Jancewicz K., Porębna W. Point cloud does matter. Selected issues of using airborne LiDAR elevation data in geomorphometric studies of rugged sandstone terrain under forest—Case study from Central Europe. Geomorphology. 2022. Vol. 412. 108316. DOI: 10.1016/j.geomorph.2022.108316
14. Chuanfa Chen, Yixuan Bei, Yanyan Li, Weiwei Zhou. Effect of interpolation methods on quantifying terrain surface roughness under different data densities. Geomorphology. 2022. Vol. 417. 108448. DOI: 10.1016/j.geomorph.2022.108448
15. Menshikov S. N., Dzhalyabov A. A., Vasilev G. G., Leonovich I. A., Ermilov O. M. Spatial Models Developed Using Laser Scanning at Gas Condensate Fields in the Northern Construction-Climatic Zone. Journal of Mining Institute. 2019. Vol. 238. pp. 430–437.
16. Gusev V. N., Blishchenko A. A., Sannikova A. P. Study of a set of factors influencing the error of surveying mine facilities using a geodesic quadcopter. Journal of Mining Institute. 2022. Vol. 254. pp. 173–179.
17.Altaeva A. A., Shamganova L. S., Zhirnov A. A. Digital simulation of the Orlov deposit surface using geoinformation technologies. Gornyi Zhurnal. 2019. No. 4. pp. 77–80. DOI: 10.17580/gzh.2019.04.17
18. Kremcheev E. A., Danilov A. S., Smirnov Yu. D. Metrological support of monitoring systems based on unmanned aerial vehicles. Journal of Mining Institute. 2019. Vol. 235. pp. 96–105.
19. Liuru Hu, Navarro-Hernández M. I., Xiaojie Liu, Tomás R., Xinming Tan g, et al. Analysis of regional large-gradient land subsidence in the Alto Guadalentín Basin (Spain) using open-access aerial LiDAR datasets. Remote Sensing of Environment. 2022. Vol. 280. 113218. DOI: 10.1016/j.rse.2022.113218
20. Sennov A. S., Mukhametdinov A. V., Myasichenko A. I., Kalugin A. V. Application of information technologies in the analyses of groundwater in the Upper Kama Potash–Magnesium Salt Deposits. Gornyi Zhurnal. 2021. No. 4. pp. 63–68. DOI: 10.17580/gzh.2021.04.09
21. Zemenkova M. Yu., Chizhevskaya E. L., Zemenkov Yu. D. Intelligent monitoring of the condition of hydrocarbon pipeline transport facilities using neural network technologies. Journal of Mining Institute. 2022. Vol. 258. pp. 933–944.
22. Jin H., Mountrakis G. Fusion of optical, radar and waveform LiDAR observations for land cover classification. ISPRS Journal of Photogrammetry and Remote Sensing. 2022. Vol. 187. pp. 171–190.
23. Pisarenko M. V. The anticipated movement and perforations of the earth surface forecast the use of the GIS technologies. GIAB. 2009. Special issue 17. Kuzbass-2. pp. 310–315.
24. Verbilo P. E., Iovlev G. A., Petrov N. E., Pavlenko G. D. Application of information modeling technologies for surveying support of mining operations. GIAB. 2022. No. 6-2. pp. 60–79.
25. Petrova T. A., Astapenka T. S., Kologrivko A.A., Esman N. M. Reducing the geoenvironmental impact of halite waste storage. GIAB. 2022. No. 10-1. pp. 155–162.
26. Kutepova N. A., Moseykin V. V., Kondakova V. N., Pospehov G. B., Straupnik I. A. Specificity of properties of coal processing waste regarding their storage. GIAB. 2022. No. 12. pp. 77–93.
27. Jaballah M., Camenen B., Paquier A., Jodeau M. An optimized use of limited ground based topographic data for river applications. International Journal of Sediment Research. 2019. Vol. 34, Iss. 3. pp. 216–225.
28. Huxiong Li, Weiya Ye, Jun Liu, Weikai Tan, Saied Pirasteh et al. High-Resolution Terrain Modeling Using Airborne LiDAR Data with Transfer Learning. Remote Sensing. 2021. Vol. 13, Iss. 17. 3448. DOI: 10.3390/rs13173448
29. Das R. K., Samanta S., Jana S. K., Rosa R. Polynomial interpolation methods in development of local geoid model. The Egyptian Journal of Remote Sensing and Space Sciences. 2018. Vol. 21, Iss. 3. pp. 265–271.
30. Ahmed H. M., Mohamed E. A., Bahaa S. A. Evaluating two numerical methods for developing a local geoid model and a local digital elevation model for the Red Sea Coast, Egypt. Journal of King Saud University–Engineering Sciences. 2021. DOI: 10.1016/j.jksues.2021.04.004
31. Banasik P., Bujakowski K. The use of quasigeoid in leveling through terrain obstacles. Reports on Geodesy and Geoinformatics. 2017. Vol. 104. pp. 57–64.
32. Borowski Ł., Banaś M. The Best Robust Estimation Method to Determine Local Surface. Baltic Journal of Modern Computing. 2019. Vol. 7, No. 4. pp. 525–540.
33. Amodio A. M., Aucelli P. P. C., Garfi V., Rosskopf C. M. Digital photogrammetric analysis approaches for the realization of detailed terrain models. Rendiconti Online della Società Geologica Italiana. 2020. Vol. 52. pp. 69–75.
34. Maan Habib, Yazan Alzubi, Ahmad Malkawi, Mohammad Awwad. Impact of interpolation techniques on the accuracy of large-scale digital elevation model. Open Geosciences. 2020. Vol. 12. pp. 190–202.
35. Boreggio M., Bernard M., Gregoretti C. Evaluating the Differences of Gridding Techniques for Digital Elevation Models Generation and Their Influence on the Modeling of Stony Debris Flows Routing: A Case Study from Rovina di Cancia Basin (North-Eastern Italian Alps). Frontiers in Earth Science. 2018. Vol. 6. 89. DOI: 10.3389/feart.2018.00089
36. Agüera-Vega F., Agüera-Puntas M., Martínez-Carricondo P., Mancini F., Carvajal F. Effects of point cloud density, interpolation method and grid size on derived Digital Terrain Model accuracy at micro topogr aphy level. International Journal of Remote Sensing. 2020. Vol. 41, Iss. 21. pp. 8281–8299.
37. Cățeanu M., Ciubotaru A. Accuracy of Ground Surface Interpolation from Airborne Laser Scanning (ALS) Data in Dense Forest Cover. ISPRS International Journal of Geo-Information. 2020. Vol. 9, Iss. 4. 224. DOI: 10.3390/ijgi9040224
38. Szabó Z., Tóth C. A., Holb I., Szabó S. Aerial Laser Scanning Data as a Source of Terrain Modeling in a Fluvial Environment: Biasing Factors of Terrain Height Accuracy. Sensors. 2020. Vol. 20, Iss. 7. 2063. DOI: 10.3390/s20072063
39. Wojciech M. Kriging Method Optimization for the Process of DTM Creation Based on Huge Data Sets Obtained from MBESs. Geosciences. 2018. Vol. 8, No. 12. 433. DOI: 10.3390/geosciences8120433
40. Chuanfa Chen, Yuan Gao, Yanyan Li, Yixuan Bei. Structure tensor-based interpolation for the derivation of accurate digital elevation models. Catena. 2022. Vol. 208. 105733. DOI: 10.1016/j.catena.2021.105733
41. Arun P. V. A compara tive analysis of different DEM interpolation methods. The Egyptian Journal of Remote Sensing and Space Sciences. 2013. Vol. 16, Iss. 2. pp. 133–139.
42. Stereńczak K., Ciesiel ski M., Bałazy R., Zawiła-Niedźwiecki T. Comparison of various algorithms for DTM interpolation from LIDAR data in dense mountain forests. European Journal of Remote Sensing. 2016. Vol. 49. pp. 599–621.
43. Ibrahim P. O., Sternberg H., Samaila-Ija H. A., Adgidzi D., Nwadialor I. J. Modeling topobathymetric surface using a triangulation irregular network (TIN) of Tunga Dam in Nigeria. Applied Geomatics. 2023. Vol. 15. pp. 281–293.
44. Jordan G. Adaptive smoothing of valleys in DEMs using TIN interpolation from ridgeline elevations: An application to morphotectonic aspect analysis. Computers & Geosciences. 2007. Vol. 33, Iss. 4. pp. 573–585.
45. Maduako Nnamdi Ikechukwu, Elijah Ebinne, Ufot Idorenyin, Ndukwu Ike Raphael. Accuracy Assessment and Comparative Analysis of IDW, Spline and Kriging in Spatial Interpolation of Landform (Topography): An Experimental Study. Journal of Geographic Information System. 2017. Vol. 9, No. 3. pp. 354–371.
46. Valkov V. A., Vinogradov K. P., Valkova E. O., Mustafin M. G. Creating highly informative rasters based on laser scanning and aerial photography data. Geodeziya i kartografiya. 2022. No. 11. pp. 40–49.
47. Instruction on observations of rock and earth surface movement during the underground mining of ore deposits. Moscow : Nedra, 1988. 112 p.

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